"CodeQL for Code Auditing" matching MCP servers:

Enables Claude Code to search, browse, and read its own past conversation history across all projects using BM25 keyword search.

Your coding agent remembers how it solved past tasks and reuses it next time: trigger, steps, outcome, lessons. Hooks recall the right skill before a task; skills strengthen with confirmed use and unused ones decay. Local SQLite, no API key, nothing leaves your machine. 9 MCP tools, works with Claude Code, Codex and Cursor. Agent-written memory stays untrusted until you approve it.

A persistent memory layer for Claude Code agents: five MCP tools (recall, remember, session, distill, status) over a markdown vault, SQLite FTS5 and an optional self-hosted Hindsight vector store, so an agent remembers facts, decisions and corrections across sessions.

Indexes codebases cut at function and class boundaries into Oracle AI Database 26ai, letting AI coding tools search code by name or meaning, trace callers, callees and change impact, read per-module wiki pages, and recall facts from earlier sessions. All of it is served over the Model Context Protocol with embeddings computed in-database, so no source code leaves the machine and no API key is required.

Local memory for coding agents that can refuse, not only recall. A rule carrying a machine-checkable proof blocks the matching command before it runs, while prose-only rules can warn but never block.

A tiny MCP server that wraps Perseus Vault to provide persistent, encrypted, local-first memory for OpenAI Codex agents, enabling them to remember project conventions, decisions, and context across sessions.

Free Industry 4.0 / IIoT tools, no API key or account: lint MQTT Sparkplug B topics, check a Unified Namespace (UNS) for naming and hierarchy problems, and run an industrial AI-readiness diagnostic for manufacturing digital transformation and smart-factory projects. Works in Claude Code, Codex and any MCP client.

Context Mode is an MCP server that reduces context window waste by sandboxing data-heavy tools, tracking session state in SQLite, and promoting code-based analysis over raw data reads, achieving up to 98% context savings.

An MCP server that preserves LLM context by intercepting large data outputs and returning only concise summaries or relevant sections. It enables efficient sandboxed code execution, file processing, and documentation indexing across multiple programming languages and authenticated CLIs.

Stop paying for your agent to rediscover what other agents already figured out. Prior is a shared knowledge base where agents exchange proven solutions — one search can save 10 minutes of trial-and-error and thousands of tokens. Your Sonnet gets access to solutions that Opus spent 20 tool calls discovering. Search is free with feedback, and contributing earns credits.

Provides persistent, client-side-encrypted memory for AI coding assistants via SAIHM, enabling tools to remember, recall, and forget with provable erasure.

Shared, code-grounded memory for developers and their coding agents. Capture a learning once and the whole team plus every agent recalls it; memory is grounded in your code and stored as git-tracked JSON reviewed in PRs, with citations validated on write and stale memory withheld from recall. Works with any MCP client.

MCP server that indexes a knowledge base of past bugs and fixes, making them searchable via BM25 from Claude Code or any MCP client.

Gives coding agents a memory of codebases by searching repositories using semantic similarity and structural call/import graphs, enabling reuse of proven patterns and reducing token usage.

Provides access to ODEI's constitutional knowledge graph, AI safety guardrails, and EVM smart contract auditing tools. It enables users to query structured domain nodes, validate agent actions, and perform security audits directly through an MCP client.

Enables persistent, project-scoped memory for OpenAI Codex Desktop and CLI on Windows, capturing prompts and responses through managed hooks, with federated recall across projects and optional local graph extraction.

MCP server for reading Claude Code session history from the local filesystem, exposing project and session data to MCP-compatible clients.

An MCP server that enables users to retrieve, filter, and search through Claude Code conversation history stored in local projects. It provides tools for listing projects and sessions, paginating through message history, and searching across conversations with keyword filtering.

Enables AI assistants to maintain persistent understanding of code projects across chat sessions via a SQLite brain that caches structural maps, summaries, and decisions. Provides tools for querying project structure, searching code, and recording insights to reduce token usage and avoid re-analysis.

MARM MCP provides persistent memory and structured session context beneath any AI tool, so your agents learn, remember, and collaborate across all your workflows.

Code intelligence MCP server for Claude Code providing multi-project code graph, semantic search, session history, knowledge base, and web search.

MCP server for the DYNAMIS doctrine system, providing access to expert knowledge on launches and sales, including resources for indices, skills, tensions, and tools for searching, auditing, and benchmarking.

Team-aware memory for AI coding assistants that tracks intent, records decisions, and surfaces real-time team conflicts before commit.

Team-aware memory for AI coding assistants that tracks intent, records decisions, and detects real-time conflicts before commit.

A personal code snippet library for Claude, enabling saving, searching, and managing code snippets across sessions and projects.

MCP server providing structured continuity memory for AI coding agents, tracking decisions, open loops, and session state in local SQLite. Enables agents to resume work from verified state across sessions without replaying transcripts.

A semantic search engine for files and code.

Independent MCP server for tracking food inventory, estimating best-before dates, managing consumption, and returning expiry reminders to MCP clients.

Knowledge graph for token-efficient code reviews. Builds a structural map of your codebase with Tree-sitter, tracks changes incrementally, and gives AI agents precise context via MCP tools. Features fixed multi-word search, qualified call resolution, dual-mode embedding (ONNX local + LiteLLM cloud), and output pagination.

Local deterministic BM25 memory for AI agents — offline-first, no API key, SHA-256 content-addressed shards, stdio MCP transport. Same query always returns the same ranked result.