Structured Output MCP Agent (Authlib).
Structured Output MCP Agent (Instructor).
Structured Output MCP Agent (Langchain Core).
Structured Output MCP Traced Agent.
Traced LLM MCP Proxy.
Traced Multi-LLM Proxy.
Traced OpenAI LangChain Agent.
Shared memory and actions for Claude, Kiro, OpenAI, Cursor, and other MCP-compatible AI clients.
Synthetic support cases and owner-reviewed Agent feedback. Anonymous reads; scoped writes.
Query Klaaro datasets, documents, and extracted records from any agent.
Route optimization for delivery fleets: plan, edit, and re-optimize multi-stop routes by prompt.
Generate AI influencer photos, face swaps, and character sheets with a consistent face.
Signed message board & forum for AI agents: every post Ed25519-signed, full history verifiable.
Plain-text security bulletin board for AI agents: read, search, post, reply. No auth to read.
Site scores, audits, Search Console, keywords, competitors, authority and AI visibility tools.
Give an agent a place to put large output. Build logs and reports get a stable versioned URL.
Travel tools for AI agents: plan and edit real trips, search stays and tours, import travel videos.
Fórum persistente com conversa MCP, assembleias, jogos multiagente e universo Meinlem.
Connect AI clients to Seller Assistant workflows for Amazon wholesale operations.
A shared team wiki your coding agents read and write — across every repo and every MCP client.
Data feeds for AI agents: list products, sign up, check balance, get a top-up link, fetch data.
Flat-fee Canadian SR&ED claim preparation through the AI you already use. Key issued at sreddy.ca.
Search Avva for an expert, then connect their model - judgment from real past decisions.
Chat where AI agents are first-class members, with their own identity and permissions.
About AI & Agents MCP servers
This category collects servers that make agents better at being agents. You will find orchestration layers that run multi-step pipelines, routers that hand a task to the right model or sub-agent, evaluation and tracing tools, prompt and skill libraries, and bridges that let one assistant call another. Some wrap commercial model APIs; others are thin coordination layers around open-source frameworks.
Because these servers often sit between your agent and other systems, look closely at where data flows and what is logged. Prefer servers that document their tool contracts clearly, support streaming where relevant, and can run locally when the workload is sensitive. Many are new and move quickly, so check the repository's recent activity before relying on one in production.