# codebase-memory-mcp: C-powered Code Intelligence MCP Server

> codebase-memory-mcp is a high-performance C-language MCP Server designed for rapid code intelligence. It indexes codebases into a persistent knowledge graph, offering sub-millisecond queries and drastically reduced token usage for AI agents. Developers needing fast, dependency-free code analysis will find its MCP integration particularly useful.

**Published:** 2026-08-05T12:00:46.552+00:00

**Keywords:** codebase-memory-mcp,mcp-server,code-intelligence,c-language,knowledge-graph

# codebase-memory-mcp: High-Performance Code Intelligence for MCP Agents

The `codebase-memory-mcp` server, written in C, provides high-performance code intelligence by indexing codebases into a persistent knowledge graph. It processes average repositories in milliseconds, supports 158 languages, and delivers sub-millisecond queries, achieving 99% fewer tokens for AI interactions. This server compiles into a single static binary with zero dependencies, making it a lean and efficient choice for integrating deep code understanding into your MCP-powered workflows.

## Integrating codebase-memory-mcp with Your MCP Client

Connecting `codebase-memory-mcp` to your MCP agent is straightforward, exposing 14 distinct tools for code analysis and interaction. For clients like Claude Desktop, you can configure it globally or per-project.

To manually configure, add the following JSON snippet to `~/.claude/.mcp.json` (for global access) or your project's `.mcp.json`:

```json
{
  "mcpServers": {
    "codebase-memory-mcp": {
      "command": "/path/to/codebase-memory-mcp",
      "args": []
    }
  }
}
```

After adding this configuration, restart your agent. You can verify the integration by running `/mcp` in your client, which should list `codebase-memory-mcp` and its available tools.

## Codebase Analysis and Querying Capabilities

`codebase-memory-mcp` offers a suite of tools for deep code analysis and efficient querying, all accessible via its MCP integration.

### Graph & Analysis Tools

The server constructs a detailed knowledge graph of your codebase, enabling sophisticated analysis:

*   **`get_architecture`**: Provides a comprehensive architecture overview, including languages, packages, entry points, routes, hotspots, boundaries, layers, and clusters.
*   **`manage_adr`**: Facilitates the persistence of architectural decisions across sessions.
*   **Louvain community detection**: Identifies functional modules by clustering call edges within the codebase.
*   **`detect_changes`**: Maps uncommitted Git changes to affected symbols, complete with risk classification.
*   **Call graph**: Resolves function calls across files and packages, supporting import-aware and type-inferred resolution.
*   **Dead code detection**: Pinpoints functions with no callers, excluding designated entry points.
*   **Cypher-like queries**: Allows structured queries against the graph, such as `MATCH (f:Function)-[:CALLS]->(g) WHERE f.name = 'main' RETURN g.name` to find functions called by 'main'.

### Search Capabilities

Beyond graph analysis, `codebase-memory-mcp` provides multiple search modalities:

*   **`semantic_query`**: Performs vector search across the entire knowledge graph. This is powered by bundled Nomic `nomic-embed-code` embeddings (40K tokens, 768d int8), compiled directly into the binary, requiring no external API keys, Ollama, or Docker. It uses an 11-signal combined scoring mechanism, incorporating TF-IDF, RRI, API/Type/Decorator signatures, AST profiles, data flow, Halstead-lite, MinHash, module proximity, and graph diffusion.
*   **BM25 full-text search**: Leverages SQLite FTS5 with a `cbm_camel_split` tokenizer, which is aware of `camelCase` and `snake_case` conventions.
*   **`search_graph`**: Enables structural search using regex name patterns, label filters, min/max degree, and file scoping.
*   **`search_code`**: Offers graph-augmented grep over indexed files.

## Server Configuration

You can manage `codebase-memory-mcp`'s behavior directly via its command-line interface. For example, to configure auto-indexing:

```bash
codebase-memory-mcp config list                          # show all settings
codebase-memory-mcp config set auto_index true           # auto-index on session start
codebase-memory-mcp config set auto_index_limit 50000    # max files for auto-index
codebase-memory-mcp config reset auto_index              # reset to default
```

These settings allow you to control how the server indexes your codebases, optimizing for your specific needs. The ability to auto-index on session start, with a configurable file limit, ensures that your MCP agent always has an up-to-date understanding of the codebase without manual intervention.

## References
- [codebase-memory-mcp on GitHub](https://github.com/DeusData/codebase-memory-mcp)
- [Model Context Protocol Documentation](https://modelcontextprotocol.io/introduction)
- [codebase-memory-mcp on model-context-protocol.com](https://model-context-protocol.com/servers/)

## Related Repository

- [codebase-memory-mcp](https://model-context-protocol.com/servers/codebase-memory-mcp)

**Source:** https://model-context-protocol.com/blog/codebase-memory-mcp-c-powered-code-intelligence-mcp-server-mcp-server-guide