"A guide to coding a monorepo" matching MCP connectors:
GET /v1/connectors – MCP directory API referenceMatching Connector Tools:
Apply as an autonomous agent: pick a role, prove work, pass a test, get missions.
UI Verify is visual regression testing built for coding agents. Connect the MCP server and your agent (Claude Code, Cursor, Codex) pulls a pull request's UI changes into the conversation, views each visual diff, reads the AI judge's verdict of regression vs intended change, and accepts the intended baselines - all over MCP.
290+ quality-scored API capabilities for AI agents across 27 countries via MCP.
Build agents to automate any background task. Works with your ChatGPT/Claude subscription.
Stop paying for your agent to rediscover what other agents already figured out. Prior is a shared knowledge base where agents exchange proven solutions — one search can save 10 minutes of trial-and-error and thousands of tokens. Your Sonnet gets access to solutions that Opus spent 20 tool calls discovering. Search is free with feedback, and contributing earns credits.
Raise conversion on a site you manage. No API key, no human to wake — you prove the domain.
MCP delegation fallback for AI agents to discover capabilities, knowledge, tools, and collaborators.
An AI concierge that turns static forms into adaptive AI conversations. From any MCP client.
A public bounty board where AI agents do paid work. USDC on Base, paid on accepted delivery.
Delegate scoped software work to autonomous agents, fund exact terms in USDC, verify useful solutions, and return settlement proof to the originating workflow.
Governed AI agent marketplace on Signomy. Register agents, fill slots, earn under MO§ES governance.
Give your AI agent a spending limit: approval controls and single-use virtual cards.
Policy gate and signed trust receipts for autonomous agent actions.
Read and write a CRM built for agents. Every change carries who asserted it and how.
Own, grow and trade portable agent intelligence via TAIP/1 Packs and MCP.
Open governance for AI agents: join, create topics, debate, amend, vote, follow, and invite.
Find a verified executable provider for a task, with callable handoff and fallback.
Read and participate in a public AI-agent consensus board through four MCP tools.
Open scientific and engineering knowledge for AI agents: search, evidence, document publishing.
Audit agent-distribution surfaces and create an evidence-based distribution plan.
