"Enhance AI Coding Accuracy in Windsurf Code Editor by Codeium" matching MCP servers:

Provides AI coding assistants with code search, impact analysis, task chaining, and persistent memory to turn AI demos into deliverable code.

Enables AI agents and MCP clients to drive real Chrome, Edge, Brave, and Firefox browsers through native automation protocols. It exposes tools for navigation, page snapshots, form filling, clicks, screenshots, console/network inspection, and tab management.

A persistent, Git-versioned map of your whole codebase and database schema that coding agents read before they touch anything. Local-first MCP server + CLI in Go: a governed repository index of code knowledge that gives Claude Code, Codex, Cursor, and opencode long-term context, memory, and code intelligence.

Enables coding agents to develop on one machine and verify results on another, using branch-bound runbooks, isolated checkpoints, and structured receipts to guide repair iterations.

MCP server that provides AI coding assistants with access to call graphs, data flows, and security analysis for multi-file vulnerability detection.

Turns a codebase into a queryable graph with semantic search, call graphs, and control/data flow analysis, served to AI coding agents via the Model Context Protocol.

Enables AI coding agents to discover whether anyone has shared a solution to a Coding Challenge and in which language, listing challenges and filtering solutions by language.

An MCP server to create secure code sandbox environment for executing code within Docker containers.

A local MCP server that indexes codebases into Neo4j and provides tools for code analysis, dependency visualization, and impact assessment.

An MCP server for fast local source code searching using Zoekt, enabling regex and substring queries across indexed directories.

AI modifies a function but misses 5 callers that also need updating. crag fixes this — it builds precise call graphs via static analysis, so AI knows exactly what's affected before making changes.

Agent memory for facts that change. When a user corrects something, Recall replaces the old fact, tells the agent what it replaced, and keeps the old value in a history. Ask what was believed on any date, see every change to a fact, or diff two dates. Runs locally on polign_db, Postgres with pgvector, MongoDB, or Qdrant. Apache 2.0.

Provides persistent, searchable memory across AI coding agent and chat history (Claude Code, Codex, Gemini CLI, ChatGPT, and more) via retrieval-augmented generation, enabling semantic and hybrid search to retain context across sessions.

MCP server for browser debugging, inspection, and verification that streams console logs, network errors, and user actions into AI coding assistants.

An MCP bridge that lets Codex and Claude Code interact with OpenLinker agents, and allows the host to serve as a callable agent in the OpenLinker network.

RegressGuard is an MCP server that records a known-good baseline and lets AI coding agents detect regressions (broken API contracts, failing tests, schema changes) during their edit loop, allowing them to self-correct before committing.

Stop runaway agents. One gateway in front of all your agent traffic — MCP tools and LLM models — one budget, one kill switch. Sits between AI clients (Cursor, Claude Desktop, Windsurf) and remote MCP servers / OpenAI-compatible model APIs; hard token budgets; a single static Go binary.

Provides coding agents with real-time, code-aware functionality to locate relevant files and search code within a repository based on bug reports or queries.

An MCP server that provides persistent memory for AI agents, enabling context retention across sessions and supporting vibe-loop workflows where agent promises and deliverables are tracked and validated.

Zabbix MCP server and CLI in one Go binary. 15 task-shaped tools: current problems, host investigation, why an alert did or did not arrive, metrics, maintenance. Zabbix 6.4+.