minga-graph
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Alternatives to minga-graph
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- AlicenseNot gradedqualityCmaintenanceA 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.90 PyPI1MIT
- AlicenseNot gradedqualityCmaintenanceEnables coding agents to query a deterministic AST knowledge graph of a codebase over MCP—finding symbols, callers/callees, dependencies, impact, and relevant tests via compact path:line JSON—so they can navigate code without grepping, embeddings, or an LLM.MIT
- AlicenseNot gradedqualityBmaintenanceEnables AI coding agents to query a local code graph over stdio, so they can see what a Git change may affect, find related tests, routes and nodes, and cite evidence paths — read-only and fully on-machine.6 npmMIT
- AlicenseNot gradedqualityAmaintenanceEnables AI coding agents to query a locally indexed structural code graph — source entities, callers/callees, Git relationships and recorded mistakes — so they retrieve focused, token-bounded context instead of reading entire files. It runs over local SQLite and can be served through a CLI, agent hooks, an MCP executable and an authenticated local dashboard.24 npmMIT
- AlicenseNot gradedqualityAmaintenanceEnables AI coding agents to query a local structural code graph, inspect relationships and impact, and retrieve focused project context before reading full files.24 npmMIT
- AlicenseNot gradedqualityBmaintenanceEnables coding agents to query a local, multi-repo code graph for symbol exploration, blast radius analysis, co-change mining, and durable code-anchored memory via MCP tools.128 npm16Business Source 1.1
TDQS
Scored across 5 tools
Each tool targets a distinct operation: explain one node, path between two, transitive impact, graph metadata, and natural-language query. graph_explain and graph_query could be mildly confused since both return node/edge info, but the 'one specific node' vs 'plain-language question' framing helps separate them.
All five tools follow the same graph_<verb/noun> pattern (graph_explain, graph_path, graph_impact, graph_stats, graph_query). Predictable and easy to scan.
Five focused tools for a read-only graph knowledge service; each earns its place without redundancy or thinness.
Covers node inspection, traversal, dependency analysis, metadata, and semantic query—full read-only lifecycle for a graph service. A direct node-list/lookup-by-name operation could be a minor convenience gap, but graph_query largely compensates.