"Creating a Graph on Vector Knowledge Base Using CozoDB" matching MCP servers:

A lean, local knowledge graph that joins a repo's code to its aSPARK delivery artifacts, enabling agents to trace user stories to code and assess impact of changes, served over MCP.

A knowledge graph MCP server that indexes your codebase into a local SQLite graph and provides tools for project mapping, file summaries, and impact analysis, drastically reducing token usage in AI coding assistants.

A local knowledge graph of your codebase for Claude Code on macOS, exposing structural data via MCP tools for querying calls, imports, test coverage, and impact analysis.

Enables semantic code search over a local codebase using Qdrant vector embeddings and OpenAI embeddings, allowing natural language queries from MCP-compatible clients like Claude Desktop.

A CLI-first semantic code search tool with MCP integration for AI assistants, enabling semantic search, AST-aware parsing, and code analysis across 13 languages.

A self-contained, in-memory graph database for AI Agents. Provides semantic code understanding through the Model Context Protocol (MCP).

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

A local MCP server for AI coding agents that builds a queryable knowledge graph of files and symbols, enforces edit scope before file writes, and records append-only reasoning logs to explain changes.

Enables exploring a C++17 coroutine and device-domain call graph through MCP tools, providing symbol search, caller/callee queries, and neighborhood exploration of coroutine-aware codebases.

A validation layer for AI coding assistants that enforces explicit LLM evaluations on plans, code diffs, and tests to ensure safer and higher-quality code.

A high-performance code knowledge graph server implementing MCP, indexing codebases into a structured AST knowledge graph with semantic search, call graph traversal, and HTTP route tracing.

Enables AI coding assistants to query a persistent local code graph for targeted context, blast-radius analysis, and incremental updates, so they read only relevant files during reviews and large-repo workflows.

Enables querying a TypeScript codebase's graph for call flows, type relationships, and symbol locations without reading file bodies.

A function-level call-graph indexer for GDScript/Godot projects, exposed as an MCP server so AI coding assistants can answer questions like 'what calls this function?' or 'what would break if I change this signal?' without re-reading the whole codebase.

Enables Claude Code to query a TypeScript dependency graph and retrieve the minimal set of files needed for code review, implementation, or debugging.

A TypeScript code graph tool with MCP integration that enables AI agents to perform semantic search and graph traversal (call graphs, paths between symbols) across a codebase.

Turns a codebase into a queryable graph with semantic search, call graphs, and control/data flow analysis, served to AI coding agents via the Model Context Protocol.

Builds rich code graphs from TypeScript/NestJS codebases using AST analysis and Neo4j, enabling semantic search, natural language querying, and intelligent graph traversal to provide deep contextual understanding of code relationships and dependencies.

Transforms code repositories and development documentation into a queryable Neo4j knowledge graph, enabling AI assistants to perform intelligent code analysis, dependency mapping, impact assessment, and automated documentation generation across 15+ programming languages.