# What Queries Can Be Performed on the codebase-memory-mcp Knowledge Graph > Explore the codebase-memory-mcp knowledge graph. Discover how to perform semantic vector search, OpenCypher pattern matching, call-path tracing, and more with eleven distinct MCP tools. Analyze your codebase effectively. - Repository: [Martin Vogel/codebase-memory-mcp](https://github.com/DeusData/codebase-memory-mcp) - Tags: api-reference - Published: 2026-07-15 --- **The codebase-memory-mcp project exposes eleven distinct MCP tools that enable semantic vector search, structural graph filtering, OpenCypher pattern matching, call-path tracing, change impact analysis, and source code retrieval against its persistent knowledge graph.** The DeusData/codebase-memory-mcp repository builds a persistent knowledge graph representing every symbol, file, package, and runtime artifact in a codebase. Developers interact with this graph through a suite of built-in MCP (Model Context Protocol) tools, each mapping to a specific query pattern implemented in the C core. These queries range from vector-similarity lookups to complex graph traversals, all executable via JSON-RPC or the CLI. ## Semantic Vector Search ### Natural Language Code Discovery The `semantic_query` tool performs vector-based similarity search across the entire graph using bundled **Nomic embeddings**—requiring no external API calls. This allows you to find functionally similar code snippets using natural language or partial code examples, matching on semantic meaning rather than literal text. ```bash codebase-memory-mcp cli semantic_query '{"project":"my-project","query":"def process_order(order):"}' ``` ## Structural Node Discovery ### Labeled Node Filtering `search_graph` executes regex, label, and degree-filtered searches for specific node types such as functions, classes, or HTTP routes. It supports pagination via `limit` and `offset` parameters for large result sets. ```bash codebase-memory-mcp cli search_graph '{"project":"my-project","label":"Function","name_pattern":"Handler"}' ``` ### Full-Text Code Search `search_code` provides grep-style text search limited to indexed files, backed by **SQLite FTS5** with a camel-case aware tokenizer. This is ideal for locating literal strings like `TODO` comments or specific variable names. ```bash codebase-memory-mcp cli search_code '{"project":"my-project","text":"TODO"}' ``` ## Graph Traversal and Path Analysis ### Call Chain Tracing `trace_path` performs a **breadth-first traversal** of `CALLS` edges to reveal inbound, outbound, or bidirectional dependencies for any function. You can specify traversal depth from 1 to 5 levels to map immediate callers or deep dependency chains. ```bash codebase-memory-mcp cli trace_path '{"project":"my-project","function_name":"process_order","direction":"both"}' ``` ### OpenCypher Pattern Matching `query_graph` exposes a read-only subset of **OpenCypher** for arbitrary graph exploration. You can write `MATCH … WHERE … RETURN` queries to traverse relationships, aggregate metrics, and filter complex patterns. ```bash codebase-memory-mcp cli query_graph '{"project":"my-project","query":"MATCH (f:Function)-[:CALLS]->(g) RETURN g.name, count(*) AS cnt ORDER BY cnt DESC LIMIT 5"}' ``` ## Impact Analysis and Change Detection ### Blast Radius Calculation `detect_changes` maps a Git diff onto graph symbols to classify the **blast radius** of modifications as high-, medium-, or low-risk. This helps reviewers understand which downstream components are affected by a commit before merging. ```bash codebase-memory-mcp cli detect_changes '{"project":"my-project","git_ref":"HEAD"}' ``` ## Schema Introspection and Metadata ### Graph Schema Discovery `get_graph_schema` returns node and edge counts, relationship patterns, and property definitions for each label. Use this to understand the graph structure before writing complex queries. ```bash codebase-memory-mcp cli get_graph_schema '{"project":"my-project"}' ``` ### Architecture Overview `get_architecture` generates a high-level summary including languages, packages, entry points, HTTP routes, hotspots, clusters, and Architecture Decision Records (ADRs). ```bash codebase-memory-mcp cli get_architecture '{"project":"my-project"}' ``` ## Content Retrieval and Documentation ### Source Code Extraction `get_code_snippet` retrieves the complete source code of a function or method given its fully-qualified name (e.g., `my_pkg.utils.process_order`). ```bash codebase-memory-mcp cli get_code_snippet '{"project":"my-project","qualified_name":"my_pkg.utils.process_order"}' ``` ### ADR Management `manage_adr` provides CRUD operations for **Architecture Decision Records** stored within the graph itself, allowing versioned documentation to live alongside the code structure. ```bash codebase-memory-mcp cli manage_adr '{"project":"my-project","action":"create","title":"Switch to SQLite","content":"We use SQLite for the graph store …"}' ``` ## Runtime Integration ### Trace Ingestion `ingest_traces` imports execution traces from APM tools or log files to validate or enrich `HTTP_CALLS` edges, bridging the gap between static analysis and runtime behavior. ```bash codebase-memory-mcp cli ingest_traces '{"project":"my-project","trace_file":"trace.ndjson"}' ``` ## Implementation Architecture According to the source code in [`internal/cbm/cbm.c`](https://github.com/DeusData/codebase-memory-mcp/blob/main/internal/cbm/cbm.c) and [`internal/cbm/cbm.h`](https://github.com/DeusData/codebase-memory-mcp/blob/main/internal/cbm/cbm.h), the C core provides fast in-memory graph traversal with sub-millisecond latency for typical queries. The OpenCypher engine in the `cypher/` directory handles parsing and execution for the `query_graph` tool, while optional persistent storage uses SQLite. All tools register with the MCP JSON-RPC server defined in the core files, making them available to both automated systems and the interactive 3-D visualization UI in [`graph-ui/index.html`](https://github.com/DeusData/codebase-memory-mcp/blob/main/graph-ui/index.html). ## Summary - **Eleven query tools** cover semantic search, structural filtering, graph traversal, impact analysis, and documentation management. - **Vector search** uses local Nomic embeddings without external API dependencies. - **Traversal queries** support up to 5 levels of breadth-first call-chain analysis. - **OpenCypher subset** enables custom pattern matching via `query_graph`. - **Performance** targets sub-millisecond response times for in-memory traversals, backed by the C core implementation in [`cbm.c`](https://github.com/DeusData/codebase-memory-mcp/blob/main/cbm.c). ## Frequently Asked Questions ### What query languages are supported by the knowledge graph? The graph supports a read-only subset of **OpenCypher** through the `query_graph` tool, allowing `MATCH`, `WHERE`, and `RETURN` clauses. Additionally, specialized tools like `search_graph` and `trace_path` provide higher-level abstractions for common patterns without requiring Cypher syntax. ### Does semantic search require an internet connection or API keys? No. According to the README and source implementation, `semantic_query` uses **bundled Nomic embeddings** that run locally. This design ensures that semantic similarity search works offline with no external API dependencies or token costs. ### How fast are graph traversals in codebase-memory-mcp? The C core implementation in [`internal/cbm/cbm.c`](https://github.com/DeusData/codebase-memory-mcp/blob/main/internal/cbm/cbm.c) provides **in-memory graph traversal** with typical query latency under 1 millisecond. Persistent storage uses SQLite for durability, but hot paths remain in memory for performance. ### Can I query the graph without running the MCP server? Yes. All MCP tools are exposed through the CLI interface using `codebase-memory-mcp cli `. The CLI invokes the same underlying C functions defined in [`cbm.c`](https://github.com/DeusData/codebase-memory-mcp/blob/main/cbm.c), making it suitable for scripts and CI/CD pipelines without requiring a running JSON-RPC server.