diff --git a/mellea/backends/huggingface.py b/mellea/backends/huggingface.py
index 48e745438..26ffb43cd 100644
--- a/mellea/backends/huggingface.py
+++ b/mellea/backends/huggingface.py
@@ -40,6 +40,7 @@
     ModelOutputThunk,
     Requirement,
 )
+from ..core.base import AbstractMelleaTool
 from ..formatters import ChatFormatter, TemplateFormatter
 from ..helpers import message_to_openai_message, messages_to_docs, send_to_queue
 from ..stdlib.components import Intrinsic, Message
@@ -564,7 +565,7 @@ async def _generate_from_context_with_kv_cache(
             ctx_as_chat = to_chat(action, ctx, self.formatter, system_prompt)
 
             # Append tool call information if applicable.
-            tools: dict[str, Callable] = dict()
+            tools: dict[str, AbstractMelleaTool] = dict()
             if tool_calls:
                 if _format:
                     FancyLogger.get_logger().warning(
@@ -723,7 +724,7 @@ async def _generate_from_context_standard(
             ctx_as_chat = to_chat(action, ctx, self.formatter, system_prompt)
 
             # Append tool call information if applicable.
-            tools: dict[str, Callable] = dict()
+            tools: dict[str, AbstractMelleaTool] = dict()
             if tool_calls:
                 if _format:
                     FancyLogger.get_logger().warning(
@@ -883,7 +884,7 @@ async def post_processing(
         conversation: list[dict],
         _format: type[BaseModelSubclass] | None,
         tool_calls: bool,
-        tools: dict[str, Callable],
+        tools: dict[str, AbstractMelleaTool],
         seed,
         input_ids,
     ):
diff --git a/mellea/backends/litellm.py b/mellea/backends/litellm.py
index 4dc82da87..226251ce2 100644
--- a/mellea/backends/litellm.py
+++ b/mellea/backends/litellm.py
@@ -24,6 +24,7 @@
     ModelOutputThunk,
     ModelToolCall,
 )
+from ..core.base import AbstractMelleaTool
 from ..formatters import ChatFormatter, TemplateFormatter
 from ..helpers import (
     chat_completion_delta_merge,
@@ -400,7 +401,7 @@ async def post_processing(
         self,
         mot: ModelOutputThunk,
         conversation: list[dict],
-        tools: dict[str, Callable],
+        tools: dict[str, AbstractMelleaTool],
         thinking,
         _format,
     ):
@@ -457,8 +458,8 @@ async def post_processing(
     @staticmethod
     def _extract_tools(
         action, _format, model_opts, tool_calls, ctx
-    ) -> dict[str, Callable]:
-        tools: dict[str, Callable] = dict()
+    ) -> dict[str, AbstractMelleaTool]:
+        tools: dict[str, AbstractMelleaTool] = dict()
         if tool_calls:
             if _format:
                 FancyLogger.get_logger().warning(
@@ -579,7 +580,7 @@ async def generate_from_raw(
 
     def _extract_model_tool_requests(
         self,
-        tools: dict[str, Callable],
+        tools: dict[str, AbstractMelleaTool],
         chat_response: litellm.ModelResponse,  # type: ignore
     ) -> dict[str, ModelToolCall] | None:
         model_tool_calls: dict[str, ModelToolCall] = {}
diff --git a/mellea/backends/ollama.py b/mellea/backends/ollama.py
index 1c0c9a201..d20e2aa17 100644
--- a/mellea/backends/ollama.py
+++ b/mellea/backends/ollama.py
@@ -22,6 +22,7 @@
     ModelOutputThunk,
     ModelToolCall,
 )
+from ..core.base import AbstractMelleaTool
 from ..formatters import ChatFormatter, TemplateFormatter
 from ..helpers import ClientCache, get_current_event_loop, send_to_queue
 from ..stdlib.components import Message
@@ -322,7 +323,7 @@ async def generate_from_chat_context(
         )
 
         # Append tool call information if applicable.
-        tools: dict[str, Callable] = dict()
+        tools: dict[str, AbstractMelleaTool] = dict()
         if tool_calls:
             if _format:
                 FancyLogger.get_logger().warning(
@@ -343,7 +344,7 @@ async def generate_from_chat_context(
         ] = self._async_client.chat(
             model=self._get_ollama_model_id(),
             messages=conversation,
-            tools=list(tools.values()),
+            tools=[t.as_json_tool for t in tools.values()],
             think=model_opts.get(ModelOption.THINKING, None),
             stream=model_opts.get(ModelOption.STREAM, False),
             options=self._make_backend_specific_and_remove(model_opts),
@@ -499,7 +500,7 @@ async def generate_from_raw(
         return results
 
     def _extract_model_tool_requests(
-        self, tools: dict[str, Callable], chat_response: ollama.ChatResponse
+        self, tools: dict[str, AbstractMelleaTool], chat_response: ollama.ChatResponse
     ) -> dict[str, ModelToolCall] | None:
         model_tool_calls: dict[str, ModelToolCall] = {}
 
@@ -525,7 +526,7 @@ async def processing(
         self,
         mot: ModelOutputThunk,
         chunk: ollama.ChatResponse,
-        tools: dict[str, Callable],
+        tools: dict[str, AbstractMelleaTool],
     ):
         """Called during generation to add information from a single ChatResponse to the ModelOutputThunk."""
         if mot._thinking is None:
@@ -557,7 +558,7 @@ async def post_processing(
         self,
         mot: ModelOutputThunk,
         conversation: list[dict],
-        tools: dict[str, Callable],
+        tools: dict[str, AbstractMelleaTool],
         _format,
     ):
         """Called when generation is done."""
diff --git a/mellea/backends/openai.py b/mellea/backends/openai.py
index d7eb284d7..8ad7796e4 100644
--- a/mellea/backends/openai.py
+++ b/mellea/backends/openai.py
@@ -28,6 +28,7 @@
     ModelOutputThunk,
     Requirement,
 )
+from ..core.base import AbstractMelleaTool
 from ..formatters import ChatFormatter, TemplateFormatter
 from ..helpers import (
     ClientCache,
@@ -591,7 +592,7 @@ async def _generate_from_chat_context_standard(
                 }
 
         # Append tool call information if applicable.
-        tools: dict[str, Callable] = dict()
+        tools: dict[str, AbstractMelleaTool] = dict()
         if tool_calls:
             if _format:
                 FancyLogger.get_logger().warning(
@@ -713,7 +714,7 @@ async def processing(
     async def post_processing(
         self,
         mot: ModelOutputThunk,
-        tools: dict[str, Callable],
+        tools: dict[str, AbstractMelleaTool],
         conversation: list[dict],
         thinking,
         seed,
diff --git a/mellea/backends/tools.py b/mellea/backends/tools.py
index 93b02fd76..32b565286 100644
--- a/mellea/backends/tools.py
+++ b/mellea/backends/tools.py
@@ -1,4 +1,4 @@
-"""Utilities for dealing with tools."""
+"""Utilities for dealing with LLM tools."""
 
 import inspect
 import json
@@ -9,12 +9,88 @@
 
 from pydantic import BaseModel, ConfigDict, Field
 
+from mellea.core.utils import FancyLogger
+
 from ..core import CBlock, Component, TemplateRepresentation
+from ..core.base import AbstractMelleaTool
 from .model_options import ModelOption
 
 
+class MelleaTool(AbstractMelleaTool):
+    """Tool class to represent a tool."""
+
+    # Tool is what we pass as a model option / as input
+    # Our ModelToolCall is the class that has a reference to the tool and actually calls with arguments
+
+    name: str
+    _as_json_tool: dict[str, Any]
+    _call_tool: Callable[..., Any]
+
+    def __init__(
+        self, name: str, tool_call: Callable, as_json_tool: dict[str, Any]
+    ) -> None:
+        """Initialize the tool with a name, tool call and as_json_tool dict."""
+        self.name = name
+        self._as_json_tool = as_json_tool
+        self._call_tool = tool_call
+
+    def run(self, *args, **kwargs) -> Any:
+        """Run the tool with the given arguments."""
+        return self._call_tool(*args, **kwargs)
+
+    @property
+    def as_json_tool(self) -> dict[str, Any]:
+        """Return the tool converted to a OpenAI compatible JSON object."""
+        return self._as_json_tool
+
+    @classmethod
+    def from_langchain(cls, tool: Any):
+        """Create a Tool from a langchain tool object."""
+        try:
+            from langchain_core.tools import BaseTool
+            from langchain_core.utils.function_calling import convert_to_openai_tool
+
+            if isinstance(tool, BaseTool):
+                tool_name = tool.name
+                as_json = convert_to_openai_tool(tool)
+
+                def parameter_remapper(*args, **kwargs):
+                    """Langchain tools expect their first argument to be 'tool_input'."""
+                    if args is not None or len(args) != 0:
+                        # This shouldn't happen. Our ModelToolCall.call_func actually passes in everything as kwargs.
+                        FancyLogger.get_logger().warning(
+                            f"ignoring unexpected args while calling langchain tool ({tool_name}): ({args})"
+                        )
+
+                    return tool.run(tool_input={**kwargs})
+
+                tool_call = parameter_remapper
+                return MelleaTool(tool_name, tool_call, as_json)
+            else:
+                raise ValueError(
+                    f"tool parameter must be a langchain tool type; got: {type(tool)}"
+                )
+
+        except ImportError as e:
+            raise ImportError(
+                f"It appears you are attempting to utilize a langchain tool '{type(tool)}'"
+                "Please install langchain core: pip install 'langchain_core'."
+            ) from e
+
+    @classmethod
+    def from_callable(cls, func: Callable, name: str | None = None):
+        """Create a Tool from a callable."""
+        # Use the function name if the name is '' or None.
+        tool_name = name or func.__name__
+        as_json = convert_function_to_ollama_tool(func, tool_name).model_dump(
+            exclude_none=True
+        )
+        tool_call = func
+        return MelleaTool(tool_name, tool_call, as_json)
+
+
 def add_tools_from_model_options(
-    tools_dict: dict[str, Callable], model_options: dict[str, Any]
+    tools_dict: dict[str, AbstractMelleaTool], model_options: dict[str, Any]
 ):
     """If model_options has tools, add those tools to the tools_dict."""
     model_opts_tools = model_options.get(ModelOption.TOOLS, None)
@@ -23,30 +99,31 @@ def add_tools_from_model_options(
 
     # Mappings are iterable.
     assert isinstance(model_opts_tools, Iterable), (
-        "ModelOption.TOOLS must be a list of Callables or dict[str, Callable]"
+        "ModelOption.TOOLS must be a list of Tool or dict[str, Tool]"
     )
 
     if isinstance(model_opts_tools, Mapping):
         # Handle the dict case.
-        for func_name, func in model_opts_tools.items():
-            assert isinstance(func_name, str), (
-                f"If ModelOption.TOOLS is a dict, it must be a dict of [str, Callable]; found {type(func_name)} as the key instead"
+        for tool_name, tool_instance in model_opts_tools.items():
+            assert isinstance(tool_name, str), (
+                f"If ModelOption.TOOLS is a dict, it must be a dict of [str, Tool]; found {type(tool_name)} as the key instead"
             )
-            assert callable(func), (
-                f"If ModelOption.TOOLS is a dict, it must be a dict of [str, Callable]; found {type(func)} as the value instead"
+            assert isinstance(tool_instance, MelleaTool), (
+                f"If ModelOption.TOOLS is a dict, it must be a dict of [str, Tool]; found {type(tool_instance)} as the value instead"
             )
-            tools_dict[func_name] = func
+            tools_dict[tool_name] = tool_instance
     else:
         # Handle any other iterable / list here.
-        for func in model_opts_tools:
-            assert callable(func), (
-                f"If ModelOption.TOOLS is a list, it must be a list of Callables; found {type(func)}"
+        for tool_instance in model_opts_tools:
+            assert isinstance(tool_instance, MelleaTool), (
+                f"If ModelOption.TOOLS is a list, it must be a list of Tool; found {type(tool_instance)}"
             )
-            tools_dict[func.__name__] = func
+            tools_dict[tool_instance.name] = tool_instance
 
 
 def add_tools_from_context_actions(
-    tools_dict: dict[str, Callable], ctx_actions: list[Component | CBlock] | None
+    tools_dict: dict[str, AbstractMelleaTool],
+    ctx_actions: list[Component | CBlock] | None,
 ):
     """If any of the actions in ctx_actions have tools in their template_representation, add those to the tools_dict."""
     if ctx_actions is None:
@@ -64,7 +141,7 @@ def add_tools_from_context_actions(
             tools_dict[tool_name] = func
 
 
-def convert_tools_to_json(tools: dict[str, Callable]) -> list[dict]:
+def convert_tools_to_json(tools: dict[str, AbstractMelleaTool]) -> list[dict]:
     """Convert tools to json dict representation.
 
     Notes:
@@ -72,16 +149,7 @@ def convert_tools_to_json(tools: dict[str, Callable]) -> list[dict]:
     - WatsonxAI uses `from langchain_ibm.chat_models import convert_to_openai_tool` in their demos, but it gives the same values.
     - OpenAI uses the same format / schema.
     """
-    converted: list[dict[str, Any]] = []
-    for tool in tools.values():
-        try:
-            converted.append(
-                convert_function_to_tool(tool).model_dump(exclude_none=True)
-            )
-        except Exception:
-            pass
-
-    return converted
+    return [t.as_json_tool for t in tools.values()]
 
 
 def json_extraction(text: str) -> Generator[dict, None, None]:
@@ -209,7 +277,7 @@ def __contains__(self, key: str) -> bool:
         >>> msg['tool_calls'] = None
         >>> 'tool_calls' in msg
         True
-        >>> tool = Tool()
+        >>> tool = OllamaTool()
         >>> 'type' in tool
         True
         """
@@ -240,7 +308,7 @@ def get(self, key: str, default: Any = None) -> Any:
 
 
 # https://github.com/ollama/ollama-python/blob/60e7b2f9ce710eeb57ef2986c46ea612ae7516af/ollama/_types.py#L337-L363
-class Tool(SubscriptableBaseModel):
+class OllamaTool(SubscriptableBaseModel):
     """Class imported from Ollama."""
 
     type: str | None = "function"
@@ -323,7 +391,9 @@ def _parse_docstring(doc_string: str | None) -> dict[str, str]:
 
 
 # https://github.com/ollama/ollama-python/blob/60e7b2f9ce710eeb57ef2986c46ea612ae7516af/ollama/_utils.py#L56-L90
-def convert_function_to_tool(func: Callable) -> Tool:
+def convert_function_to_ollama_tool(
+    func: Callable, name: str | None = None
+) -> OllamaTool:
     """Imported from Ollama."""
     doc_string_hash = str(hash(inspect.getdoc(func)))
     parsed_docstring = _parse_docstring(inspect.getdoc(func))
@@ -356,13 +426,13 @@ def convert_function_to_tool(func: Callable) -> Tool:
             "type": ", ".join(types),
         }
 
-    tool = Tool(
+    tool = OllamaTool(
         type="function",
-        function=Tool.Function(
-            name=func.__name__,
+        function=OllamaTool.Function(
+            name=name or func.__name__,
             description=schema.get("description", ""),
-            parameters=Tool.Function.Parameters(**schema),
+            parameters=OllamaTool.Function.Parameters(**schema),
         ),
     )
 
-    return Tool.model_validate(tool)
+    return OllamaTool.model_validate(tool)
diff --git a/mellea/backends/utils.py b/mellea/backends/utils.py
index 7ecca2ff2..2c3c00f6d 100644
--- a/mellea/backends/utils.py
+++ b/mellea/backends/utils.py
@@ -6,6 +6,7 @@
 from collections.abc import Callable
 
 from ..core import CBlock, Component, Context, FancyLogger, ModelToolCall
+from ..core.base import AbstractMelleaTool
 from ..formatters import ChatFormatter
 from ..stdlib.components import Message
 from .tools import parse_tools
@@ -56,7 +57,7 @@ def to_chat(
 
 
 def to_tool_calls(
-    tools: dict[str, Callable], decoded_result: str
+    tools: dict[str, AbstractMelleaTool], decoded_result: str
 ) -> dict[str, ModelToolCall] | None:
     """Parse a tool call string."""
     model_tool_calls: dict[str, ModelToolCall] = dict()
@@ -70,8 +71,8 @@ def to_tool_calls(
 
         # Clean up the function args slightly. Some models seem to
         # hallucinate parameters when none are required.
-        sig = inspect.signature(func)
-        if len(sig.parameters) == 0:
+        param_map = func.as_json_tool["function"]["parameters"]["properties"]
+        if len(param_map) == 0:
             tool_args = {}
 
         model_tool_calls[tool_name] = ModelToolCall(tool_name, func, tool_args)
diff --git a/mellea/backends/vllm.py b/mellea/backends/vllm.py
index c2fac0ee7..4ba2efe3c 100644
--- a/mellea/backends/vllm.py
+++ b/mellea/backends/vllm.py
@@ -36,6 +36,7 @@
     GenerateType,
     ModelOutputThunk,
 )
+from ..core.base import AbstractMelleaTool
 from ..formatters import ChatFormatter, TemplateFormatter
 from ..helpers import get_current_event_loop, send_to_queue
 from .backend import FormatterBackend
@@ -280,7 +281,7 @@ async def _generate_from_context_standard(
             ctx_as_chat = to_chat(action, ctx, self.formatter, system_prompt)
 
             # Append tool call information if applicable.
-            tools: dict[str, Callable] = dict()
+            tools: dict[str, AbstractMelleaTool] = dict()
             if tool_calls:
                 if _format:
                     FancyLogger.get_logger().warning(
@@ -388,7 +389,7 @@ async def post_processing(
         conversation: list[dict],
         _format: type[BaseModelSubclass] | None,
         tool_calls: bool,
-        tools: dict[str, Callable],
+        tools: dict[str, AbstractMelleaTool],
         seed,
     ):
         """Called when generation is done."""
diff --git a/mellea/backends/watsonx.py b/mellea/backends/watsonx.py
index 58004c4ce..31093c026 100644
--- a/mellea/backends/watsonx.py
+++ b/mellea/backends/watsonx.py
@@ -27,6 +27,7 @@
     ModelOutputThunk,
     ModelToolCall,
 )
+from ..core.base import AbstractMelleaTool
 from ..formatters import ChatFormatter, TemplateFormatter
 from ..helpers import (
     ClientCache,
@@ -309,7 +310,7 @@ async def generate_from_chat_context(
             model_opts["response_format"] = {"type": "text"}
 
         # Append tool call information if applicable.
-        tools: dict[str, Callable] = {}
+        tools: dict[str, AbstractMelleaTool] = {}
         if tool_calls:
             if _format:
                 FancyLogger.get_logger().warning(
@@ -433,7 +434,7 @@ async def post_processing(
         self,
         mot: ModelOutputThunk,
         conversation: list[dict],
-        tools: dict[str, Callable],
+        tools: dict[str, AbstractMelleaTool],
         seed,
         _format,
     ):
@@ -573,7 +574,7 @@ async def generate_from_raw(
         return results
 
     def _extract_model_tool_requests(
-        self, tools: dict[str, Callable], chat_response: dict
+        self, tools: dict[str, AbstractMelleaTool], chat_response: dict
     ) -> dict[str, ModelToolCall] | None:
         model_tool_calls: dict[str, ModelToolCall] = {}
         for tool_call in chat_response["choices"][0]["message"].get("tool_calls", []):
diff --git a/mellea/core/base.py b/mellea/core/base.py
index 3ab7c4ece..9c601bbe0 100644
--- a/mellea/core/base.py
+++ b/mellea/core/base.py
@@ -562,6 +562,19 @@ def view_for_generation(self) -> list[Component | CBlock] | None:
         ...
 
 
+class AbstractMelleaTool(abc.ABC):
+    """Abstract base class for Mellea Tool."""
+
+    @abc.abstractmethod
+    def run(self, *args, **kwargs) -> Any:
+        """Runs the tool on the given arguments."""
+
+    @property
+    @abc.abstractmethod
+    def as_json_tool(self) -> dict[str, Any]:
+        """Provides a JSON description for Mellea Tool."""
+
+
 @dataclass
 class TemplateRepresentation:
     """Representing a component as a set of important attributes that can be consumed by the formatter."""
@@ -571,7 +584,7 @@ class TemplateRepresentation:
         str,
         str | Component | CBlock | Iterable | Mapping | TemplateRepresentation | None,
     ]
-    tools: dict[str, Callable] | None = (
+    tools: dict[str, AbstractMelleaTool] | None = (
         None  # the key must be the name of the function.
     )
     fields: list[Any] | None = None
@@ -607,12 +620,12 @@ class ModelToolCall:
     """
 
     name: str
-    func: Callable
+    func: AbstractMelleaTool
     args: Mapping[str, Any]
 
     def call_func(self) -> Any:
         """A helper function for calling the function/tool represented by this object."""
-        return self.func(**self.args)
+        return self.func.run(**self.args)
 
 
 def blockify(s: str | CBlock | Component) -> CBlock | Component:
diff --git a/mellea/helpers/openai_compatible_helpers.py b/mellea/helpers/openai_compatible_helpers.py
index 4462c1e8c..7374b157f 100644
--- a/mellea/helpers/openai_compatible_helpers.py
+++ b/mellea/helpers/openai_compatible_helpers.py
@@ -5,11 +5,12 @@
 from typing import Any
 
 from ..core import FancyLogger, ModelToolCall
+from ..core.base import AbstractMelleaTool
 from ..stdlib.components import Document, Message
 
 
 def extract_model_tool_requests(
-    tools: dict[str, Callable], response: dict[str, Any]
+    tools: dict[str, AbstractMelleaTool], response: dict[str, Any]
 ) -> dict[str, ModelToolCall] | None:
     """Extracts tool calls from the dict representation of an OpenAI-like chat response object."""
     model_tool_calls: dict[str, ModelToolCall] = {}
diff --git a/mellea/stdlib/components/docs/richdocument.py b/mellea/stdlib/components/docs/richdocument.py
index 75bcb60c7..67bcb01fa 100644
--- a/mellea/stdlib/components/docs/richdocument.py
+++ b/mellea/stdlib/components/docs/richdocument.py
@@ -11,6 +11,7 @@
 from docling_core.types.doc.document import DoclingDocument, TableItem
 from docling_core.types.io import DocumentStream
 
+from ....backends.tools import MelleaTool
 from ....core import CBlock, Component, ModelOutputThunk, TemplateRepresentation
 from ..mobject import MObject, Query, Transform
 
@@ -191,7 +192,10 @@ def format_for_llm(self) -> TemplateRepresentation | str:
         return TemplateRepresentation(
             args={"table": self.to_markdown()},
             obj=self,
-            tools=self._get_all_members(),
+            tools={
+                k: MelleaTool.from_callable(c)
+                for k, c in self._get_all_members().items()
+            },
             fields=[],
             template="{{table}}",
             template_order=None,
diff --git a/mellea/stdlib/components/mify.py b/mellea/stdlib/components/mify.py
index 8bbfcb350..2ef6baa31 100644
--- a/mellea/stdlib/components/mify.py
+++ b/mellea/stdlib/components/mify.py
@@ -5,6 +5,7 @@
 from collections.abc import Callable
 from typing import Any, Protocol, TypeVar, overload, runtime_checkable
 
+from ...backends.tools import MelleaTool
 from ...core import (
     CBlock,
     Component,
@@ -192,7 +193,10 @@ def format_for_llm(self) -> TemplateRepresentation:
         return TemplateRepresentation(
             args=args,  # type: ignore
             obj=self,
-            tools=self._get_all_members(),
+            tools={
+                k: MelleaTool.from_callable(c)
+                for k, c in self._get_all_members().items()
+            },
             fields=[],
             template=self._template,
             template_order=template_order,
diff --git a/mellea/stdlib/components/mobject.py b/mellea/stdlib/components/mobject.py
index 3ab48c040..b5dc25f87 100644
--- a/mellea/stdlib/components/mobject.py
+++ b/mellea/stdlib/components/mobject.py
@@ -6,6 +6,7 @@
 from collections.abc import Callable
 from typing import Protocol, runtime_checkable
 
+from ...backends.tools import MelleaTool
 from ...core import CBlock, Component, ModelOutputThunk, TemplateRepresentation
 
 
@@ -223,10 +224,13 @@ def format_for_llm(self) -> TemplateRepresentation | str:
         parsing for tools and fields. The content is retrieved
         from `content_as_string()`.
         """
+        tools = {
+            k: MelleaTool.from_callable(c) for k, c in self._get_all_members().items()
+        }
         return TemplateRepresentation(
             args={"content": self.content_as_string()},
             obj=self,
-            tools=self._get_all_members(),
+            tools=tools,
             fields=[],
             template_order=["*", "MObject"],
         )
diff --git a/pyproject.toml b/pyproject.toml
index 2536834d6..a9c1ec0fb 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -118,6 +118,7 @@ dev = [
     "mypy>=1.17.0",
     "python-semantic-release~=7.32",
     "nbmake>=1.5.5",
+    "langchain-core>=1.2.7", # Necessary for mypy and some tool tests
 ]
 
 notebook = [
diff --git a/test/backends/test_huggingface_tools.py b/test/backends/test_huggingface_tools.py
index 9bbd097ba..6aa3a317a 100644
--- a/test/backends/test_huggingface_tools.py
+++ b/test/backends/test_huggingface_tools.py
@@ -2,6 +2,8 @@
 
 import pytest
 
+from mellea.backends.tools import MelleaTool
+
 # Skip entire module in CI since the single test is qualitative
 pytestmark = [
     pytest.mark.huggingface,
@@ -56,7 +58,7 @@ def get_temperature(location: str) -> int:
     output = session.instruct(
         "What is today's temperature in Boston? Answer in Celsius. Reply the number only.",
         model_options={
-            ModelOption.TOOLS: [get_temperature],
+            ModelOption.TOOLS: [MelleaTool.from_callable(get_temperature)],
             ModelOption.MAX_NEW_TOKENS: 1000,
         },
         tool_calls=True,
diff --git a/test/backends/test_mellea_tool.py b/test/backends/test_mellea_tool.py
new file mode 100644
index 000000000..9449c5fbe
--- /dev/null
+++ b/test/backends/test_mellea_tool.py
@@ -0,0 +1,123 @@
+import pytest
+from langchain_core.tools import Tool, tool
+from pydantic_core import ValidationError
+
+import mellea
+from mellea.backends.model_options import ModelOption
+from mellea.backends.tools import MelleaTool
+from mellea.stdlib.session import MelleaSession
+
+
+def callable(input: int) -> str:
+    """Common callable to test tool functionality."""
+    return str(input)
+
+
+@tool
+def langchain_tool(input: int) -> str:
+    """Common langchain tool to test functionality."""
+    return str(input)
+
+
+@pytest.fixture(scope="module")
+def session():
+    return mellea.start_session()
+
+
+def test_from_callable():
+    t = MelleaTool.from_callable(callable)
+    assert isinstance(t, MelleaTool)
+    assert t.name == callable.__name__
+
+    name_override = "new_name"
+    t = MelleaTool.from_callable(callable, name_override)
+    assert t.name == name_override
+
+    assert t.as_json_tool is not None
+    expected_t_json = {
+        "type": "function",
+        "function": {
+            "name": "new_name",
+            "description": "Common callable to test tool functionality.",
+            "parameters": {
+                "type": "object",
+                "required": ["input"],
+                "properties": {"input": {"type": "integer", "description": ""}},
+            },
+        },
+    }
+    assert t.as_json_tool == expected_t_json
+
+    assert t.run(1) == "1"
+    assert t.run(input=2) == "2"
+
+
+@pytest.mark.qualitative
+@pytest.mark.ollama
+@pytest.mark.llm
+def test_from_callable_generation(session: MelleaSession):
+    t = MelleaTool.from_callable(callable, "mellea_tool")
+
+    out = session.instruct(
+        "Call a mellea tool.",
+        model_options={ModelOption.TOOLS: [t], ModelOption.SEED: 1},
+        strategy=None,
+        tool_calls=True,
+    )
+
+    assert out.tool_calls is not None, "did not call tool when expected"
+    assert len(out.tool_calls.keys()) > 0
+
+    tool = out.tool_calls[t.name]
+    assert isinstance(tool.call_func(), str), "tool call did not yield expected type"
+
+
+def test_from_langchain():
+    t = MelleaTool.from_langchain(langchain_tool)
+    assert isinstance(t, MelleaTool)
+    assert t.name == "langchain_tool"
+
+    expected_t_json = {
+        "type": "function",
+        "function": {
+            "name": "langchain_tool",
+            "description": "Common langchain tool to test functionality.",
+            "parameters": {
+                "properties": {"input": {"type": "integer"}},
+                "required": ["input"],
+                "type": "object",
+            },
+        },
+    }
+    assert t.as_json_tool == expected_t_json
+
+    # This works for regular callables, but the indirection necessitated by langchain
+    # means it doesn't work. That's okay; generated requests don't fit this format.
+    with pytest.raises(ValidationError):
+        assert t.run("1") == "1"
+
+    assert t.run(input=2) == "2"
+
+
+@pytest.mark.qualitative
+@pytest.mark.ollama
+@pytest.mark.llm
+def test_from_langchain_generation(session: MelleaSession):
+    t = MelleaTool.from_langchain(langchain_tool)
+
+    out = session.instruct(
+        "Call a langchain tool.",
+        model_options={ModelOption.TOOLS: [t], ModelOption.SEED: 1},
+        strategy=None,
+        tool_calls=True,
+    )
+
+    assert out.tool_calls is not None, "did not call tool when expected"
+    assert len(out.tool_calls.keys()) > 0
+
+    tool = out.tool_calls[t.name]
+    assert isinstance(tool.call_func(), str), "tool call did not yield expected type"
+
+
+if __name__ == "__main__":
+    pytest.main([__file__])
diff --git a/test/backends/test_tool_calls.py b/test/backends/test_tool_calls.py
index 958dfe783..9ebf02ddd 100644
--- a/test/backends/test_tool_calls.py
+++ b/test/backends/test_tool_calls.py
@@ -4,6 +4,7 @@
 from mellea.backends.tools import (
     add_tools_from_context_actions,
     add_tools_from_model_options,
+    MelleaTool,
 )
 from mellea.backends import ModelOption
 from mellea.core import ModelOutputThunk
@@ -42,7 +43,9 @@ def test_tool_called_from_context_action(m: MelleaSession, table: Table):
     def test1(): ...
     def test2(): ...
 
-    model_opts = {ModelOption.TOOLS: [test1, test2]}
+    model_opts = {
+        ModelOption.TOOLS: [MelleaTool.from_callable(t) for t in [test1, test2]]
+    }
 
     tools = {}
 
diff --git a/test/backends/test_tool_helpers.py b/test/backends/test_tool_helpers.py
index 4441e885e..5614ac40d 100644
--- a/test/backends/test_tool_helpers.py
+++ b/test/backends/test_tool_helpers.py
@@ -2,6 +2,7 @@
 from mellea.backends.tools import (
     add_tools_from_context_actions,
     add_tools_from_model_options,
+    MelleaTool,
 )
 from mellea.backends import ModelOption
 from mellea.core import CBlock, Component, ModelOutputThunk, TemplateRepresentation
@@ -19,7 +20,9 @@ def parts(self):
 
     def format_for_llm(self) -> TemplateRepresentation:
         return TemplateRepresentation(
-            obj=self, args={"arg": None}, tools={self.tool1.__name__: self.tool1}
+            obj=self,
+            args={"arg": None},
+            tools={self.tool1.__name__: MelleaTool.from_callable(self.tool1)},
         )
 
     def _parse(self, computed: ModelOutputThunk) -> str:
@@ -36,7 +39,7 @@ def tool2(self):
     def format_for_llm(self) -> TemplateRepresentation:
         tr = super().format_for_llm()
         assert tr.tools is not None
-        tr.tools[self.tool2.__name__] = self.tool2
+        tr.tools[self.tool2.__name__] = MelleaTool.from_callable(self.tool2)
         return tr
 
 
@@ -46,15 +49,19 @@ def get_weather(location: str) -> int:
         return 21
 
     ftc = FakeToolComponent()
-    model_options = {ModelOption.TOOLS: [get_weather, ftc.tool1]}
+    model_options = {
+        ModelOption.TOOLS: [
+            MelleaTool.from_callable(t) for t in [get_weather, ftc.tool1]
+        ]
+    }
 
     tools = {}
     add_tools_from_model_options(tools, model_options)
 
-    assert tools["get_weather"] == get_weather
+    assert tools["get_weather"]._call_tool == get_weather
 
     # Must use `==` for bound methods.
-    tool1 = tools["tool1"]
+    tool1 = tools["tool1"]._call_tool
     assert tool1 == ftc.tool1, f"{tool1} should == {ftc.tool1}"
 
 
@@ -66,18 +73,18 @@ def get_weather(location: str) -> int:
     ftc = FakeToolComponent()
     model_options = {
         ModelOption.TOOLS: {
-            get_weather.__name__: get_weather,
-            ftc.tool1.__name__: ftc.tool1,
+            get_weather.__name__: MelleaTool.from_callable(get_weather),
+            ftc.tool1.__name__: MelleaTool.from_callable(ftc.tool1),
         }
     }
 
     tools = {}
     add_tools_from_model_options(tools, model_options)
 
-    assert tools["get_weather"] == get_weather
+    assert tools["get_weather"]._call_tool == get_weather
 
     # Must use `==` for bound methods.
-    tool1 = tools["tool1"]
+    tool1 = tools["tool1"]._call_tool
     assert tool1 == ftc.tool1, f"{tool1} should == {ftc.tool1}"
 
 
@@ -90,11 +97,11 @@ def test_add_tools_from_context_actions():
     add_tools_from_context_actions(tools, ctx_actions)
 
     # Check that tools with the same name get properly overwritten in order of ctx.
-    tool1 = tools["tool1"]
+    tool1 = tools["tool1"]._call_tool
     assert tool1 == ftc2.tool1, f"{tool1} should == {ftc2.tool1}"
 
     # Check that tools that aren't overwritten are still there.
-    tool2 = tools["tool2"]
+    tool2 = tools["tool2"]._call_tool
     assert tool2 == ftc1.tool2, f"{tool2} should == {ftc1.tool2}"
 
 
diff --git a/test/backends/test_vllm_tools.py b/test/backends/test_vllm_tools.py
index 2d085deb9..db8a511f3 100644
--- a/test/backends/test_vllm_tools.py
+++ b/test/backends/test_vllm_tools.py
@@ -2,6 +2,8 @@
 
 import pytest
 
+from mellea.backends.tools import MelleaTool
+
 # Skip entire module in CI since the single test is qualitative
 pytestmark = [
     pytest.mark.vllm,
@@ -64,7 +66,7 @@ def get_temperature(location: str) -> int:
     output = session.instruct(
         "What is today's temperature in Boston? Answer in Celsius. Reply the number only.",
         model_options={
-            ModelOption.TOOLS: [get_temperature],
+            ModelOption.TOOLS: [MelleaTool.from_callable(get_temperature)],
             ModelOption.MAX_NEW_TOKENS: 1000,
         },
         tool_calls=True,
diff --git a/uv.lock b/uv.lock
index c360b0f4a..7ef653bdd 100644
--- a/uv.lock
+++ b/uv.lock
@@ -2620,6 +2620,18 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/f8/62/d9ba6323b9202dd2fe166beab8a86d29465c41a0288cbe229fac60c1ab8d/jsonlines-4.0.0-py3-none-any.whl", hash = "sha256:185b334ff2ca5a91362993f42e83588a360cf95ce4b71a73548502bda52a7c55", size = 8701, upload-time = "2023-09-01T12:34:42.563Z" },
 ]
 
+[[package]]
+name = "jsonpatch"
+version = "1.33"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "jsonpointer" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/42/78/18813351fe5d63acad16aec57f94ec2b70a09e53ca98145589e185423873/jsonpatch-1.33.tar.gz", hash = "sha256:9fcd4009c41e6d12348b4a0ff2563ba56a2923a7dfee731d004e212e1ee5030c", size = 21699, upload-time = "2023-06-26T12:07:29.144Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/73/07/02e16ed01e04a374e644b575638ec7987ae846d25ad97bcc9945a3ee4b0e/jsonpatch-1.33-py2.py3-none-any.whl", hash = "sha256:0ae28c0cd062bbd8b8ecc26d7d164fbbea9652a1a3693f3b956c1eae5145dade", size = 12898, upload-time = "2023-06-16T21:01:28.466Z" },
+]
+
 [[package]]
 name = "jsonpointer"
 version = "3.0.0"
@@ -2897,6 +2909,44 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/d3/32/da7f44bcb1105d3e88a0b74ebdca50c59121d2ddf71c9e34ba47df7f3a56/keyring-25.6.0-py3-none-any.whl", hash = "sha256:552a3f7af126ece7ed5c89753650eec89c7eaae8617d0aa4d9ad2b75111266bd", size = 39085, upload-time = "2024-12-25T15:26:44.377Z" },
 ]
 
+[[package]]
+name = "langchain-core"
+version = "1.2.7"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "jsonpatch" },
+    { name = "langsmith" },
+    { name = "packaging" },
+    { name = "pydantic" },
+    { name = "pyyaml" },
+    { name = "tenacity" },
+    { name = "typing-extensions" },
+    { name = "uuid-utils" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/a2/0e/664d8d81b3493e09cbab72448d2f9d693d1fa5aa2bcc488602203a9b6da0/langchain_core-1.2.7.tar.gz", hash = "sha256:e1460639f96c352b4a41c375f25aeb8d16ffc1769499fb1c20503aad59305ced", size = 837039, upload-time = "2026-01-09T17:44:25.505Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/6e/6f/34a9fba14d191a67f7e2ee3dbce3e9b86d2fa7310e2c7f2c713583481bd2/langchain_core-1.2.7-py3-none-any.whl", hash = "sha256:452f4fef7a3d883357b22600788d37e3d8854ef29da345b7ac7099f33c31828b", size = 490232, upload-time = "2026-01-09T17:44:24.236Z" },
+]
+
+[[package]]
+name = "langsmith"
+version = "0.6.6"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "httpx" },
+    { name = "orjson", marker = "platform_python_implementation != 'PyPy'" },
+    { name = "packaging" },
+    { name = "pydantic" },
+    { name = "requests" },
+    { name = "requests-toolbelt" },
+    { name = "uuid-utils" },
+    { name = "zstandard" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/1a/3d/04a79fb7f0e72af88e26295d3b9ab88e5204eafb723a8ed3a948f8df1f19/langsmith-0.6.6.tar.gz", hash = "sha256:64ba70e7b795cff3c498fe6f2586314da1cc855471a5e5b6a357950324af3874", size = 953566, upload-time = "2026-01-27T17:37:21.166Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/81/81/62c5cc980a3f5a7476792769616792e0df8ba9c8c4730195ec700a56a962/langsmith-0.6.6-py3-none-any.whl", hash = "sha256:fe655e73b198cd00d0ecd00a26046eaf1f78cd0b2f0d94d1e5591f3143c5f592", size = 308542, upload-time = "2026-01-27T17:37:19.201Z" },
+]
+
 [[package]]
 name = "lark"
 version = "1.2.2"
@@ -3397,6 +3447,7 @@ watsonx = [
 [package.dev-dependencies]
 dev = [
     { name = "isort" },
+    { name = "langchain-core" },
     { name = "mypy" },
     { name = "nbmake" },
     { name = "pdm" },
@@ -3467,6 +3518,7 @@ provides-extras = ["hf", "vllm", "litellm", "watsonx", "docling", "all"]
 [package.metadata.requires-dev]
 dev = [
     { name = "isort", specifier = ">=6.0.0" },
+    { name = "langchain-core", specifier = ">=1.2.7" },
     { name = "mypy", specifier = ">=1.17.0" },
     { name = "nbmake", specifier = ">=1.5.5" },
     { name = "pdm", specifier = ">=2.24.0" },
@@ -4592,6 +4644,87 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/35/b5/cf25da2218910f0d6cdf7f876a06bed118c4969eacaf60a887cbaef44f44/opentelemetry_semantic_conventions_ai-0.4.13-py3-none-any.whl", hash = "sha256:883a30a6bb5deaec0d646912b5f9f6dcbb9f6f72557b73d0f2560bf25d13e2d5", size = 6080, upload-time = "2025-08-22T10:14:16.477Z" },
 ]
 
+[[package]]
+name = "orjson"
+version = "3.11.6"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/70/a3/4e09c61a5f0c521cba0bb433639610ae037437669f1a4cbc93799e731d78/orjson-3.11.6.tar.gz", hash = "sha256:0a54c72259f35299fd033042367df781c2f66d10252955ca1efb7db309b954cb", size = 6175856, upload-time = "2026-01-29T15:13:07.942Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/30/3c/098ed0e49c565fdf1ccc6a75b190115d1ca74148bf5b6ab036554a550650/orjson-3.11.6-cp310-cp310-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:a613fc37e007143d5b6286dccb1394cd114b07832417006a02b620ddd8279e37", size = 250411, upload-time = "2026-01-29T15:11:17.941Z" },
+    { url = "https://files.pythonhosted.org/packages/15/7c/cb11a360fd228ceebade03b1e8e9e138dd4b1b3b11602b72dbdad915aded/orjson-3.11.6-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:46ebee78f709d3ba7a65384cfe285bb0763157c6d2f836e7bde2f12d33a867a2", size = 138147, upload-time = "2026-01-29T15:11:19.659Z" },
+    { url = "https://files.pythonhosted.org/packages/4e/4b/e57b5c45ffe69fbef7cbd56e9f40e2dc0d5de920caafefcc6981d1a7efc5/orjson-3.11.6-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:a726fa86d2368cd57990f2bd95ef5495a6e613b08fc9585dfe121ec758fb08d1", size = 135110, upload-time = "2026-01-29T15:11:21.231Z" },
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