"Temporal" matching MCP servers:

An experimental MCP server that compresses git commit co-change coupling graphs using the Baligács temporal clique linear spanner algorithm, reducing edge and token counts by ~55-65% while preserving temporal reachability, and exposes tools like index_repository, get_architecture, search_code, and temporal_compress for querying code knowledge graphs.

A local Git intelligence MCP server that provides deep repository analytics including hotspots, temporal coupling, knowledge maps, churn analysis, and risk scoring for AI agents.

Audits local datasets and ML training code for target, temporal, and entity leakage, PII exposure, and invalid evaluation design, returning structured evidence and pass/review/block verdicts before model training.

Temporal change-impact authority MCP server that tracks per-entity change history across runs and answers downstream propagation queries, enabling impact analysis and reverification worklists.

MCP server that acts as a temporal verification firewall, checking structured assumptions or diffs against immutable version receipts to return allow/block/abstain with cited evidence.

Enables AI agents to search code by meaning, explore codebase structure, store and query knowledge with temporal facts, and read source code through a set of MCP tools.

Memtrace is a persistent memory layer for coding agents, built as a bi‑temporal structural knowledge graph over your codebase (AST‑driven symbols and relationships, plus temporal evolution and cross‑service API topology)

memex is a developer context-continuity MCP server — it watches your git repos and builds a temporal knowledge graph (modules, symbols, decisions, open problems) via Graphiti + Neo4j, then serves it to any AI coding agent over MCP. Every edge carries a validity window and a confidence score that decays over time. 12 tools across read and write. Install via npx -y stifler-memex-mcp. MIT licensed.

One install. 8 IDEs. Your agent works from a structural map of your repo instead of re-reading whole files — so sessions run longer before the context wall — and bi-temporal mistakes are auto-captured from your git revert history, so it stops repeating fixes that already failed. Context packets run ~50–90% smaller per file (structural size, not a bill saving — run engram bench on yours).