"A service for map lookup functionality" matching MCP servers:

A navigable symbol map of your codebase for coding agents, enabling efficient code navigation and reading only relevant symbols instead of entire files.

Enables code analysis of JavaScript, TypeScript, TSX, Python, and Rust files using Tree-sitter, providing symbol listing, definition/reference lookup, AST queries, LSP-style features, and SQLite indexing for efficient cross-file searches.

Compiles codebases into a layered knowledge graph, providing an MCP server with 16 tools for AI to navigate, understand, and analyze code before making changes.

Indexes Kotlin/Native platform klibs to enable fast symbol lookup for iOS APIs. Supports querying classes, members, and platform constants via MCP tools for Kotlin Multiplatform development.

An experimental MCP server that explores neuroscience-inspired approaches to software development analysis, featuring associative memory, context-aware caching, and cross-language API detection.

An MCP server for inspecting and editing StarCraft II maps and mods directly, enabling file-level manipulation of map components, triggers, scripts, and more without the Galaxy Editor UI.

An MCP server that reduces AI coding agent token usage by 80-99% through a queryable knowledge graph of code, change tracking, and persistent memory across sessions.

Enables full-text search for code declarations across multiple languages using SQLite FTS5 and universal ctags, allowing users to search for functions, classes, and other code elements.

Enables business services to push error logs and generate diagnostic reports using MCP tools for log searching, code querying, and report generation.

Analyzes JSX prop usage in React/TypeScript codebases using AST parsing, enabling prop usage tracking, component analysis, and TypeScript support.

Enables mapping JavaScript error stack traces back to original source code, extracting context information to help developers locate and fix issues.

A Model Context Protocol server that helps programmers understand code by providing explanations, tech stack analysis, and best practice suggestions through prompt templates.

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.

Turns a codebase into a persistent knowledge graph so AI coding agents can answer structural questions about functions, call chains, routes, and cross-service links through graph queries instead of reading files one by one.

Integrates Google's Gemini AI models into Claude Code and other MCP clients to provide second opinions, code comparisons, and token counting. It supports streaming responses and multi-turn conversations directly within your existing AI development workflow.

Maintains a self-updating JSON index of repository files, functions, and descriptions so agents can query relevant files instead of grepping the tree.

Provides AI agents with ground-truth knowledge of Strapi projects by reading real schema files, enabling accurate queries and safe refactoring operations.

MCP server that analyzes codebases to provide dependency graphs, impact analysis, and file insights across 15+ programming languages, enabling AI assistants to understand project structure and navigate code efficiently.

Uses Claude as an independent second-model reviewer inside Codex, performing reviews on disposable Git snapshots with structured findings.

Enables Claude Code to leverage OpenAI models for expert code review, deep architecture analysis, and security audits, with automatic markdown report generation.