# mcp

Anthropic's frontier AI assistant

Anthropic's AI assistant known for strong reasoning, nuanced writing, and extended context up to 200K tokens. Available in Opus (most capable), Sonnet (balanced), and Haiku (fast) tiers. Features web search, deep research, file analysis, code execution, artifacts, and Projects for organized workflows. Claude Code provides terminal-based agentic coding. API supports tool use, batch processing, and prompt caching. Available via claude.ai, mobile apps, and developer API.

OpenAI coding agent for app, editor, terminal, and cloud work

Codex is OpenAI's coding agent for software development across the Codex app, editor, terminal, and cloud tasks. It helps write, review, debug, refactor, and automate code, with ChatGPT plan access for managed surfaces and API-key usage for CLI, SDK, and IDE workflows. The open-source CLI and SDK support local repository work, while cloud features add GitHub review, Slack/Linear integrations, worktrees, skills, MCP, and automations.

Apple's Safari-native MCP server for web debugging agents

Safari MCP Server is Apple's safaridriver-based MCP server in Safari Technology Preview, giving compatible coding agents local access to Safari page content, console logs, network requests, screenshots, JavaScript evaluation, interactions, viewport controls, and accessibility/performance checks.

Context compression for LLM apps and coding agents

Headroom is an Apache-2.0 context compression layer for LLM apps and coding agents. It compresses tool output, logs, files, RAG chunks, and agent history through a local library, proxy, wrapper, or MCP server, with retrieval hooks for bringing originals back when needed. Treat its savings numbers as Headroom-reported benchmarks, not independent aicoolies measurements.

Codebase knowledge graph MCP server for AI coding agents

Codebase Memory MCP is an MIT-licensed MCP server that turns a repository into a persistent code knowledge graph for AI coding agents. It gives Claude Code, Cursor, Codex-style agents, and other MCP clients structural queries for functions, classes, call chains, routes, and architecture, helping them explore large projects without repeatedly rereading files or relying only on broad search.

Python and TypeScript framework for production multi-agent systems

BeeAI Framework is an Apache-2.0 toolkit for building production-ready AI agents and multi-agent systems in Python and TypeScript. Its docs cover agents, tools, RAG, memory, workflows, backend providers, serving, and A2A/MCP integration surfaces, making it a vendor-neutral option for teams comparing LangGraph, CrewAI, Mastra, and related agent runtimes.

MCP server for connecting AI assistants to Supabase projects

Supabase MCP is Supabase's Apache-2.0 server for connecting AI assistants to Supabase projects. It can expose database, configuration, and project-management workflows to MCP clients such as Cursor, Claude, and Windsurf, while the official docs emphasize permission and security review before production use, SQL changes, or high-privilege database access.

Official Notion MCP server for AI-agent workspace access

Notion MCP Server is Notion's official MIT-licensed MCP server for connecting AI assistants to Notion workspaces. It supports the vendor-backed remote OAuth path and tools designed for page, workspace, and Markdown-style operations, making it a safer default than unofficial Notion bridges for teams already using Notion for docs, projects, or internal knowledge bases.

MCP integration platform for agent tool use at scale

Klavis AI is an Apache-2.0 MCP integration platform for teams connecting AI agents to external SaaS tools and APIs. The public repo and official docs position it as infrastructure for reliable tool access at scale, so it fits teams that want reusable MCP connectors without treating every integration as a one-off script or custom OAuth maintenance project.

Open-source Firecracker sandboxes for long-running AI agents

Superserve is an open-source sandbox infrastructure layer for AI agents that need durable computers instead of short-lived shells. It runs isolated Firecracker microVMs, supports pause, resume, snapshot, fork, preview URLs, MCP connectivity, SDK/API control, Docker workloads, and self-hosting, while the hosted service adds pay-as-you-go agent sandboxes for teams.

Official authenticated remote MCP endpoint for Linear issues, projects, comments, and coding-agent workflows.

Linear MCP Server is Linear’s official authenticated remote MCP endpoint for agent access to issues, projects, and comments. It gives Claude, Codex, Cursor, VS Code, Windsurf, Zed, and other clients a centrally hosted way to find, create, and update Linear work items through OAuth-backed MCP without maintaining a local connector or brittle API glue.

Official Slack MCP server for approved workspace search, messaging, canvas, and user-context actions.

Slack MCP Server is Slack’s official remote MCP layer for giving approved AI clients workspace context and controlled actions. It lets agents search messages, files, users, and channels, draft or send messages, read threads, manage canvases, and authenticate through Slack OAuth while workspace admins approve integrations and normal Slack rate limits still apply.

Official remote MCP server for design-to-code and write-to-canvas Figma workflows.

Figma MCP Server is Figma’s official remote Model Context Protocol surface for design-to-code agents. It gives supported clients structured design context, variables, components, selected-frame code context, Code Connect mappings, and beta write-to-canvas tools for creating or updating native Figma frames from an MCP client while keeping the workflow tied to Figma files.

MCP gateway and integration catalog for AI agents

Executor is an MIT-licensed integration layer and MCP gateway for AI agents. It gives Claude Code, Cursor, Codex, and other MCP-speaking clients one endpoint for connected OpenAPI specs, GraphQL APIs, MCP servers, Google Discovery sources, and custom JavaScript tools, with local, cloud, and self-hosted deployment options for teams centralizing tool access.

Filesystem-first framework for durable AI agents

Eve is Vercel's filesystem-first TypeScript framework for building durable AI agents as ordinary project files. It combines Markdown instructions and skills, typed tools, channels, connections, subagents, schedules, sandboxes, and evals with Vercel's agent runtime so teams can ship deployable agents without hand-rolling orchestration. The current beta fits Vercel-native backend agent projects.

Read/write MCP bridge between AI coding agents and Figma

Talk to Figma MCP is an MIT-licensed bridge from Grab that connects Cursor, Claude Code, and other MCP-capable agents to Figma through a local MCP server, WebSocket bridge, and Figma plugin. Unlike read-only context servers, it can inspect selections, create or modify nodes, update text in bulk, and automate design operations, so teams should review permissions before enabling write access.

MCP server that gives coding agents structured Figma context for design-to-code work

Figma Context MCP is an MCP server for giving coding agents structured access to Figma design context during implementation. Instead of copying screenshots or hand-written design specs into prompts, teams can expose layout, component, and context information to agents such as Cursor, Claude Code, and other MCP-compatible coding workflows. It is a strong design-to-code bridge for teams trying to reduce hallucinated UI details and tighten handoff between designers and AI-assisted developers.

Open computer-use platform for browser, terminal, and full desktop automation

Coasty is an open-source computer-use platform for teams that want AI agents to operate across browser, terminal, and full desktop surfaces instead of only clicking DOM nodes. The project combines planner/orchestrator logic, visual and input control, local Electron workflows, remote sandbox options, an MCP server, and logs for debugging long-running automations. It is a strong fit for QA, research-to-action, form workflows, and repetitive desktop tasks where browser-only agents are too narrow.

State-machine guardrails for controlling which tools AI coding agents can use at each phase.

Statewright is a guardrail layer for AI coding agents that uses explicit state machines to control what an agent can do at each stage of a workflow. Instead of relying only on prompt instructions, teams can model phases such as plan, implement, test, and review, then constrain tool access for clients like Claude Code, Codex, Cursor, opencode, and related MCP workflows.

MCP-native personal context vault for keeping AI agents aligned with your work, voice, and projects.

Unabyss is a personal context headquarters for AI agents. It syncs sources such as email, Slack, Notion, Drive, meetings, and professional profiles into structured context files that can be served to MCP-capable clients. The strongest angle is not generic note taking; it is permissioned, reusable context for Claude, Cursor, custom agents, and other tools that otherwise need the same background explained repeatedly.

MCP, ACP and Skills support for building production coding agents — interactive or automated.

fast-agent is an Apache-licensed Python framework for building and running LLM agents with full MCP (Model Context Protocol) and ACP support. It ships with an interactive shell mode, Skills management, and multi-model routing — making it a practical platform for coding agents, workflow automation, and agent evaluation across Claude, Codex, HuggingFace, and local models.

Turn any MCP server, OpenAPI spec, or GraphQL endpoint into a CLI — at runtime, with zero codegen.

mcp2cli turns MCP servers, OpenAPI specs, and GraphQL endpoints into standard CLIs at runtime — no codegen, no schema bloat. Tools and arguments load only when requested via --list and --help flags, cutting up to 96–99% of the tokens that native MCP integrations waste on schema preloading. Works with Claude Code, Cursor, Codex, and any agent that can call shell commands, and ships with OAuth, stdio/HTTP/SSE transports, and a bake mode for reusable connections.

Official remote MCP server for Jira and Confluence

Atlassian's official remote MCP server connects Jira and Confluence to LLM clients, IDEs, and agent platforms over OAuth, so Claude, Cursor, and other MCP-aware tools can search issues, read pages, and post updates inside the same permission boundaries users already have. As a vendor-hosted reference implementation, it standardizes the Atlassian side of remote Model Context Protocol deployments.

Official Chrome DevTools MCP server for coding agents

chrome-devtools-mcp is the Chrome DevTools team's official MCP server that lets coding agents control and inspect a live Chrome browser with first-party Chrome DevTools Protocol fidelity. It exposes Network inspection, Performance traces, Lighthouse audits, console output, and structured DOM snapshots as typed MCP tools, so agents can debug real pages and ship reliable web performance investigations without resorting to brittle DOM scraping.