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Alternatives to gograph

  • A
    license
    Not graded
    quality
    D
    maintenance
    An MCP server that transforms codebases into knowledge graphs using Neo4J, enabling AI assistants to understand code structure, relationships, and metrics for more context-aware assistance.
    28
    MIT

Related Servers

  • A
    license
    Not graded
    quality
    A
    maintenance
    A local code-intelligence engine for AI agents that indexes repositories into a PostgreSQL-backed code graph and serves structured, token-budgeted context over MCP and HTTP, enabling targeted queries on symbols, dependencies, contracts, and impact analysis.
    7
    Apache 2.0
  • A
    license
    Not graded
    quality
    C
    maintenance
    Zero-dependency Go MCP server that indexes codebases into an embedded Kùzu graph DB—enabling 90%+ token reduction, precise call-chain queries, and AI architectural health audits.
    1
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  • A
    license
    Not graded
    quality
    B
    maintenance
    Enables AI coding agents to interrogate a local repository deterministically for symbols, dependencies, call paths, routes, tests, and Git impact, returning verified structured evidence with exact line citations instead of requiring the whole codebase to be read.
    115 PyPI
    3
    MIT
  • F
    license
    Not graded
    quality
    D
    maintenance
    A minimalist indexing tool that provides AI agents with semantic search and structural AST parsing for deep codebase understanding. It enables autonomous agents to navigate large codebases predictably using vector embeddings and native language server capabilities like definition and reference tracking.
    -
  • A
    license
    Not graded
    quality
    C
    maintenance
    A graph-powered code intelligence engine that indexes codebases into a structural knowledge graph to provide AI agents with deep context on function calls, types, and execution flows. It offers local, zero-dependency tools for hybrid search, impact analysis, and dead code detection across Python, JavaScript, and TypeScript projects.
    675 PyPI
    814
    MIT

TDQS

A4.1/5.0

Scored across 68 tools

Disambiguation3/5

Most tools target distinct analysis tasks, but several are explicit aliases or near-duplicates (gograph_trace vs gograph_errorflow, gograph_mocks vs gograph_implementers), and bundle-style tools such as context, explore, explain, plan, review, summary, and wiki overlap in scope. The descriptions provide WHEN/NOT TO USE guidance, which mitigates but does not eliminate misselection risk.

Naming Consistency5/5

All 68 tools use the same gograph_ prefix and lower_snake_case convention, including multiword names like gograph_session_create and gograph_boundaries_create. There is no mixing of camelCase, PascalCase, or inconsistent delimiter styles.

Tool Count1/5

68 tools is far beyond the 3-15 well-scoped range and exceeds the 50+ threshold for extreme mismatch. The large surface includes compatibility aliases and multiple overlapping analysis bundles, making the set unwieldy for agents despite the domain being broad.

Completeness5/5

The surface covers static Go analysis comprehensively: call graphs, dependencies, types and interfaces, SQL, routes, env vars, errors, concurrency, tests and coverage, complexity, hotspots, orphans, mutation, boundaries, API drift, changes, risk review, diagrams, docs, and session telemetry. No obvious lifecycle gap remains for the stated static-analysis purpose.

Maintenance

ActivityActive
ResponsivenessResponsive