agent-university

Agent University MCP Server

Agent University is a knowledge corpus built from real, live-verified builds ("degrees") of LLM-tooling targets — SDKs, APIs, CLIs, and cloud services. Every artifact carries an evidence tier and a source citation back to the build that produced it. The corpus is served by a hosted MCP server.

Requirements

• An Agent University API key in the AGENT_UNIVERSITY_API_KEY environment variable. The server rejects unauthenticated requests. Keys are issued by the maintainer — request one via an issue on this repo.

Register the server

Claude Code:

claude mcp add --transport http agent-university \
  https://agent-university-api-production.up.railway.app/v1/mcp \
  --header "Authorization: Bearer ${AGENT_UNIVERSITY_API_KEY}"

Any other MCP client (streamable HTTP):

{
  "url": "https://agent-university-api-production.up.railway.app/v1/mcp",
  "headers": { "Authorization": "Bearer <AGENT_UNIVERSITY_API_KEY>" }
}

How to use the tools

Building with a covered target? Call agent_university_how_to_build FIRST. It returns the complete, ordered build guide assembled from how the target was actually built and verified — verbatim source content with citations, not search snippets.

Knowledge tools:

Tool	When to use
agent_university_how_to_build	First call for any "how do I build X" task — full ordered guide.
agent_university_search	General queries; supports target/degree/artifact/evidence filters.
agent_university_plan_build	Planning context: recipes, gotchas, instructions for a target.
agent_university_get_gotchas	Before writing code against a target — known traps, live-verified.
agent_university_get_recipe	Working recipes for a target or degree.
agent_university_debug_error	Hit a platform-specific error or symptom — search known fixes.
agent_university_get_artifact	Fetch a full artifact by ID (from search results).
agent_university_get_code_sample	Fetch a code sample by ID with source citation.
agent_university_get_degree_status	Degree metadata for a target.

Ops tools (agent_university_ops_*: deployment, checks, freshness, probe, metrics, events, runbooks, runbook, error_catalog) report on the hosted API itself — corpus version, health checks, retrieval mode, error-code handling. Use them to verify the server is current before trusting results, or when a call fails: ops_freshness answers "is the corpus live and current?" in one call; ops_error_catalog says whether an error is retryable.

Recommended flow: how_to_build (or search) → get_gotchas before coding → debug_error when something breaks. Prefer artifacts marked with higher evidence tiers (e.g. live_verified) when results conflict.