"Google Pub/Sub" matching MCP servers:

Provides ROS2 workspace graph knowledge including package dependencies, message/service/action definitions, and topic pub/sub relationships through MCP tools.

Standard coding agents waste 70% of context tokens re-reading raw files with shell grep. Synapse-MCP indexes your codebase into a sub-millisecond local AST graph—giving Claude Code, Cursor, and Windsurf exact caller trees, 60% lower token spend, and zero-hallucination refactoring.

Exposes tools for AI assistants to query a persistent SQLite+FTS5 index of C/C++ symbols parsed from real build commands, enabling sub-millisecond lookup, full-text search, and natural-language explanation without hallucination.

Enables using the xAI Grok CLI as an MCP sub-agent for code review, asking questions, and continuing conversations within MCP hosts like Claude Code.

Enables AI coding agents to intelligently index and search codebases with sub-20ms retrieval, 8x memory compression, and cross-encoder reranking via MCP stdio.

A local MCP server that indexes codebases using Tree-sitter AST parsing and LanceDB, enabling AI models to search across repositories with sub-second latency.

In-memory Code Property Graph context slicer for local models (Ollama,Cursor, Claude Desktop) that extracts sub-1,200 token reachability closures for autonomous repository bug repair on consumer edge hardware (4GB–8GB VRAM) without cloud APIs.

High-performance code intelligence MCP server. Indexes codebases into a persistent knowledge graph — average repo in milliseconds. 159 languages, sub-ms queries, 99% fewer tokens. Single static binary, zero dependencies.

Sub-1ms cross-stack AST contract layer and compiler verification engine mapping React/Next.js routes to FastAPI and SQLAlchemy models for AI coding agents.

A production-ready MCP server that provides comprehensive dbt project quality assessment for any GitHub repository, enabling AI agents to analyze dbt models, check metadata coverage, and map data lineage.

Routes reverse-engineering requests by intent and target type (native binaries, Android apps, web/JS, Electron, .NET, firmware, protocols, archives, processes, UI, vulnerabilities) to the right analysis chain, orchestrating real backends such as Ghidra, JADX, apktool, adb, Frida, x64dbg, and pe-sieve with capability fallbacks and task-state tracking. Records evidence and claims in a ledger and applies three-layer verification (execution, fact, delivery), backed by an on-demand, book-style skill for guidance.

Enables AI coding agents to verify code patches locally with sub-50ms neuro-symbolic analysis, detecting structural issues like dependency cycles and interface drift without consuming output tokens.

A production-ready MCP server suite for AI agent tool integration, providing five composable tool modules: code analysis, web scraping, file operations, API integration, and data transformation.

Context Bridge is a lightweight MCP server that builds a persistent semantic knowledge graph of your codebase, enabling AI assistants to query complex codebases with sub-millisecond latency without re-reading files every session.

Model-agnostic code memory MCP server using budget-aware graph retrieval for AI agents, providing sub-millisecond queries, token budgeting, and deterministic results without embeddings or vector databases.

Enables querying and analyzing documents far larger than an LLM's context window by having the model emit constrained symbolic S-expression commands that a logic engine validates and executes, rather than generating arbitrary code. Server-side handle and memo storage keeps token usage low while supporting recursive sub-queries, multi-document context selection, and introspection of bound results.

A high-performance MCP server providing lightning-fast hybrid code search using TF-IDF and vector embeddings for AI assistants. It enables real-time codebase indexing and semantic retrieval with sub-50ms latency and offline support.

An MCP server that integrates Google Gemini CLI with Claude Code for AI-powered development assistance, enabling code review, bug analysis, feature planning, and code explanation without requiring an API key.

Self-hosted AI Agent Memory + Code Intelligence Platform providing persistent memory, AST-aware code search, and quality enforcement via a single MCP endpoint.

Enables AI coding agents to perform static security linting for issues like dynamic eval, secret leaks, and insecure regexes, plus sub-millisecond AST symbol search across large repositories through the Model Context Protocol. It offers a zero-dependency, pure ESM runtime suited to high-concurrency agent workflows.

A high-performance, polyglot code-analysis graph for coding agents that enables cross-language and cross-process code relationship queries in sub-millisecond time.

Enables analysis of documents far larger than an LLM's context window by having the model emit constrained symbolic S-expression commands that are validated and executed server-side, with large result sets and stashed context kept behind compact handle stubs rather than roundtripped as full text. Supports recursive sub-queries and memo storage so agents can search, filter, aggregate, and recall document content token-efficiently.

Search and retrieve Google Apps Script libraries with AI-generated summaries and usage examples directly from MCP clients.

Deterministic JSON repair, validation, example-generation, and schema-coercion for AI agents — zero LLM calls, sub-10ms, $0.0005 per call.

A lightweight MCP server that enhances AI agents with tools for codebase analysis, task delegation to sub-agents, multi-agent coordination through chatrooms, and project todo management.

Enables AI agents to run deterministic database intelligence tasks including natural-language-to-SQL synthesis, AST SQL auditing and optimization, schema migration diffing, SQL transpilation, index and normalization advice, PII scrubbing, fixture generation, connection-pool sizing, isolation-hazard auditing, and ORM model compilation over Streamable HTTP or stdio.

Enables developers and AI agents to compress context, plan token budgets, rerank results, patch code, analyze ASTs and dependencies, isolate stack traces, compile polyglot types, solve deterministic math, schedule constraints, judge A/B tests, and diff agent memory checkpoints through 12 specialized tools.

Local BM25/FTS5 section index for project documentation (Markdown and optional Google Docs/Sheets) that returns ~60-token section hits instead of full-file reads. Includes symbol/caller lookup across 9 languages, verified status writes, and a wiring gate that refuses to mark tasks done when target functions have zero callers.

MCP server for verifying AI agent claims vs reality — single-transcript inline grounding-check that flags when an agent's response states facts not in the input context, when its code silently swallows exceptions and substitutes mock data, or when its multi-turn transcript contains contradictions or unverified completion claims. Sub-second, local, free, no API calls.

Allows Claude Code to request an independent code review from Google Antigravity (Gemini, Claude, or GPT-OSS) via the Antigravity CLI, providing a second opinion on plans or diffs.