Make provenance and evidence traceability first-class for shared memory mcp (shared memory mcp server agentic)

[haasonsaas]

Summary

Carry source, decision, and output provenance through the main workflow so downstream agents can audit and cite it.

This issue was generated from an org-wide EvalOps mining pass on 2026-05-10 07:57 UTC. It combines live GitHub repo signals with a per-repo arXiv search. Treat the research links as grounding for a concrete implementation, not as a request for a literature review.

Repo Evidence

• Repository description: Shared Memory MCP server for agentic teams - solving coordination tax with 6x token efficiency
• Tree signals: 0 docs files, 0 workflows, 0 proto files, 1 test-like files.
• README.md:177 includes latent-spec language: ```typescript // Workers request details only when needed: expand_context_section("codebase_files") // 2K tokens
• README.md:204 includes latent-spec language: ### Dependency Resolution - declare_outputs - Declare future outputs - await_dependency - Wait for dependency
• test-workflow.ts:103 includes latent-spec language: 'No breaking changes to public APIs', 'Performance improvements should not increase memory usage by >20%' ]

Research Grounding

Repo axes: infra, governance, security, evaluation

Search keywords: mcp, server, context, session, tokens, workers, session_id, dependencies, performance, agentic, await, efficiency

• arXiv:2506.11019v1 Mind the Metrics: Patterns for Telemetry-Aware In-IDE AI Application Development using the Model Context Protocol (MCP) (Vincent Koc, Jacques Verre, Douglas Blank, Abigail Morgan), 2025.
• arXiv:2506.02032v2 Towards Secure MLOps: Surveying Attacks, Mitigation Strategies, and Research Challenges (Raj Patel, Himanshu Tripathi, Jasper Stone, Noorbakhsh Amiri Golilarz, Sudip Mittal, Shahram Rahimi), 2025.
• arXiv:2307.13473v1 Exploring MLOps Dynamics: An Experimental Analysis in a Real-World Machine Learning Project (Awadelrahman M. A. Ahmed), 2023.
• arXiv:2503.15577v1 Navigating MLOps: Insights into Maturity, Lifecycle, Tools, and Careers (Jasper Stone, Raj Patel, Farbod Ghiasi, Sudip Mittal, Shahram Rahimi), 2025.
• arXiv:2507.19570v1 MCP4EDA: LLM-Powered Model Context Protocol RTL-to-GDSII Automation with Backend Aware Synthesis Optimization (Yiting Wang, Wanghao Ye, Yexiao He, Yiran Chen, Gang Qu, Ang Li), 2025.
• arXiv:2510.09968v1 Operationalizing AI: Empirical Evidence on MLOps Practices, User Satisfaction, and Organizational Context (Stefan Pasch), 2025.
• arXiv:2512.11541v1 A Multi-Criteria Automated MLOps Pipeline for Cost-Effective Cloud-Based Classifier Retraining in Response to Data Distribution Shifts (Emmanuel K. Katalay, David O. Dimandja, Jordan F. Masakuna), 2025.
• arXiv:2302.01061v1 MLOps with enhanced performance control and observability (Indradumna Banerjee, Dinesh Ghanta, Girish Nautiyal, Pradeep Sanchana, Prateek Katageri, Atin Modi), 2023.
• arXiv:2602.18764v2 The Convergence of Schema-Guided Dialogue Systems and the Model Context Protocol (Andreas Schlapbach), 2026.
• arXiv:2604.24801v2 Architectural Observability Collapse in Transformers (Thomas Carmichael), 2026.

What To Build

• Add stable identifiers for source records, derived decisions, and emitted outputs.
• Thread those identifiers through logs/events/API responses without leaking secrets.
• Provide a query or debug surface that reconstructs the chain for one completed workflow.

Acceptance Criteria

• A short design note names the repo-specific workflow, threat or correctness model, and the research assumptions being adopted.
• A runnable check, fixture, or verifier exercises the new contract in CI or an equivalent local command documented in the repo.
• The implementation emits or stores enough evidence for a downstream agent/operator to cite inputs, decisions, and outputs.
• At least one negative/degraded-mode case is covered so failures are observable rather than silently accepted.
• Documentation links the new behavior to the relevant EvalOps platform primitive or explicitly records why this repo remains standalone.

Notes

• Generated issue 2/5 for evalops/shared-memory-mcp by evalops_org_miner.py.
• Before implementation, confirm the sampled latent-spec snippets still match main; this issue intentionally cites exact file paths/lines where the mining pass saw them.