"Fluent Bit" matching MCP servers:

Enables an agent to check its own drafted messages for the wording, leaked placeholders, and chat wrappers that make readers think a bot wrote them, returning a verdict, 0-100 score, and per-finding suggestions. It also applies the safe fixes that need no judgement and reports what still requires a human or model rewrite before anything is sent.

Enables agents to discover rooms, read conversations, register, create rooms, post messages, and reply through MCP or HTTP with bearer-token authentication.

Enables two Grok Bots to exchange messages through a shared mailbox, with send and inbox tools and webhook-based wakeups.

Enables AI agents to automate CAD/CAE/CFD and chemical/mechanical engineering workflows through 60 JSON-RPC tools, including direct COM control of SolidWorks, Aspen Plus, HYSYS, AutoCAD, and Fluent, plus headless Linux first-principles solvers with invariant circuit breaking.

Exposes Alpaca paper trading as MCP tools for checking quotes, managing a watchlist, checking market hours, and placing simulated trades.

MCP server for l402-kit — enables AI agents (Claude, Cursor, etc.) to autonomously pay Bitcoin Lightning-protected APIs. Tools: l402_fetch, l402_balance, l402_spending_report. Run with: npx l402-kit-mcp

Discover and connect your agents with other agents via A2A protocol. Share resources for free or fee.

Enables AI agents to overcome context loops by extracting and packaging code for external AI consultation or automated multi-agent collaboration, with optional ChatGPT Desktop integration.

Enables AI agents to perform go-to-market workflows such as company and contact enrichment, CRM querying, and controlled, audited writes to a CRM through MCP tools callable from any MCP client.

AgentPay — x402 crypto data gateway on Stellar. 10 live pay-per-call tools: token prices, whale activity, gas tracker, DeFi TVL, Fear & Greed, Dune queries, token security. Agents pay USDC on Stellar. No API keys. Budget-aware sessions.

A multi-agent literature review pipeline that uses specialized agents to research, peer-review, and synthesize academic and practitioner perspectives into grounded reports.

A prompt-injection-aware MCP server demonstrating guardrails for agentic tool use, including permission tiers, untrusted-content quarantine, and heuristic injection detection, with a fictional ticket-triage assistant.

An AI conversation management layer that enables creating chat sessions, persisting message history to GitHub, and performing semantic searches over past interactions. It supports multi-turn threading and context injection to integrate external memory sources into Claude conversations.

MCP coordination primitive for multi-agent workflows. Lets multiple AI coding agents (Claude Code, Cursor, n8n, custom clients) discover each other and exchange messages and tasks via a shared SQLite-backed message bus.

Enables AI agents to design hardware by writing C-like HDL and compiling it to Verilog, with real toolchain verification including synthesis checks.

Enables AI agents to interactively explore PDDL planning problems by exposing a PDDL engine as MCP tools for initialization, action execution, state inspection, and goal checking.

Just to be clear about the final JSON: the MCP server is named herdr-inbox, and it enables Claude Code agents in herdr to ask questions asynchronously without stalling, with all open questions answered from one popup and answers routed back to the asking agent.

Gives your coding agent the review comments left on a running frontend with Maple. It lists open comments with the element, source location and screenshot they point to, waits for new ones, and resolves them when the fix is in.

Enables building and running zero-dependency MCP servers with automatic JSON Schema generation, exposing Python tools to Claude Desktop, Cursor, and autonomous agent fleets.

A single-install MCP server that provides AI agents with real-time market data, DeFi intelligence, payment rails (x402/Q402), agent identity infrastructure, and self-evolution capabilities.

Enables coding agents to make offline, zero-cost decisions using schema-safe Choice/Score/Noul primitives, a confidence gatekeeper, planning, adversarial red-teaming, research, and RLVR-based self-improvement via 21 MCP tools.

Enables AI agents to publish, claim, submit, and settle tasks with each other, including automatic decomposition of complex work into subtasks assigned to specialized agents. Also provides a unified gateway to call multiple large language models (DeepSeek, Qwen, GPT, Claude, Doubao) with one API key, plus tools for agent messaging, balances, identity, and model preferences.

Enables Claude Code and Codex hosts to route work to bounded local AI subscription workers through signed-in clients, with saved workflow contracts, evidence checkpoints, reviewed model memory, video and social evidence capture, and bounded failover. Manages long-running tasks via pinned Git worktrees and an external supervisor that can swap a stopped host for another provider's client.

让AI agent雇佣人类完成物理世界的任务，如参加会议、跑腿等。

All-in-one 24-tool MCP runtime and 180-skill library providing protocol-level C4 workflow gates, cognitive reasoning engines, and safe execution for AI coding agents.

A standard, local-first MCP server that lets AI agents carry a sealed, hash-verified task manifest across turns so state drift, loops, and duplicate actions are caught before they cost tokens. It also externalizes bulky payloads into content-addressed references that can be filtered server-side and rehydrated losslessly, keeping cached prompt prefixes intact and cutting context cost.

Enables MCP agents to request human confirmation for actions via a Telegram bot. It uses a Vercel-hosted proxy and Redis to facilitate secure, real-time YES/NO approvals from a mobile device.

Provides local desktop agents with durable project memory and safety gates for writing long novels, enabling continuity management, chapter drafting, and state-aware handoffs.

Enables on-demand generation of TypeScript tools using an LLM with human-in-the-loop approval and safe sandboxed execution. It allows users to create and persist custom functionality through natural language requests.

Serves configurable fake service worlds as MCP tools with fault injection, recording every call and enabling seeded pytest assertions on final state.