"A local knowledge base" matching MCP servers:

A local knowledge graph MCP server that provides AI agents with permanent, structured memory about codebases, enabling semantic search, blast radius analysis, and convention enforcement.

Provides Claude with persistent, semantic knowledge of a codebase across sessions by maintaining a local knowledge base of structural maps, compressed file summaries, and insights.

A local MCP server that turns AI clients into power users of local git repositories, enabling clone, browse, search, and inspect code without burning API tokens.

A high-precision local knowledge base server enabling AI agents to navigate, search, and reason about complex codebases using hybrid semantic, lexical, and graph retrieval.

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.

Offers a control surface for AI agent security with four independent checks: source-code scanning, tenant isolation, LLM content verification, and deploy gating. Currently in pre-release, with no functional scanning engines yet.

A 100% local MCP server for semantic and lexical search over your code, library docs, and PDFs, featuring hybrid BM25 and dense retrieval, syntax aware chunking, and an optional code knowledge graph. It also ships a Coral integration, so you can expose your code search as SQL and join it with live data, all without anything leaving your machine.

Requirements knowledge base for coding agents, stored per Git branch in your repo, with Prolog checks for contradictions, untraced code and unproven requirements.

A local Git intelligence MCP server that provides deep repository analytics including hotspots, churn, knowledge maps, and risk scoring, all computed from commit history without data leaving your machine.

AI reads your codebase like a book - one page at a time. Pharaoh gives it the index and a map of how every chapter connects.

Indexes a mono-repo into a knowledge graph and provides MCP tools to query code structure—packages, components, routes, HTTP calls—without file reads or grep round-trips.

A local-first codebase intelligence tool that enables AI assistants to research codebases using semantic search, multi-hop relationship discovery, and structural parsing. It allows users to extract architectural patterns and institutional knowledge across 30+ programming languages through an MCP-compatible interface.

Provides a read-only interface to audit and continue coding agent sessions by extracting plans, intents, and edit authorship from history across multiple agents (Claude, Codex, OpenCode, Antigravity, Pi) via MCP, CLI, and Python SDK.

MCP server connecting Claude Code to LM Studio, delegating token-expensive tasks to a local model while keeping the cloud model in control. It reduces cloud context usage by reading files locally and returning only the processed results.

Enables building MCP servers in TypeScript where tool schemas, descriptions, and validation are automatically generated from class methods, their TypeScript types, and JSDoc comments at compile time.

A code review tool server based on Model Context Protocol (MCP) providing multi-dimensional code review and scoring.

Enables AI agents to ask read-only questions about a repository's history through GitHub APIs, including blame, path history, merge base, PR association, diffs, and file contents, with aggressive caching and no clone required.

A fully local RAG MCP server for semantic code search and code intelligence, using AST-level chunking and hybrid search to pinpoint functions, classes, and APIs. No cloud, no API keys, zero setup.

locidx

An installable MCP server that reviews diffs/PRs against a target repository's own coding conventions, learned via RAG over its code, docs, and lint config, citing specific file:line sources.