Levelupp MCP is the delivery component of the Levelupp platform — a Model Context Protocol server that injects your own expert-validated knowledge into every relevant prompt. Connect once, then forget it's there.
Levelupp speaks standard Model Context Protocol over streamable HTTP. Add it to your client, and your AI calls it automatically whenever a prompt touches your domain — no workflow change.
{ "mcpServers": { "levelupp": { "url": "https://levelupp.misikiri.com/mcp", "headers": { "X-API-Key": "lup_your_key_here" } } } }
That's the whole integration. Your API key identifies your workspace and you as a builder — issued by your workspace admin.
# Add the Levelupp connector URL — sign-in happens in the browser https://levelupp.misikiri.com/mcp # Levelupp supports OAuth 2.0 + PKCE — no key to paste, # log in with your builder account and you're connected.
# Endpoint (streamable HTTP transport) https://levelupp.misikiri.com/mcp # Auth — either header-key or OAuth 2.0 + PKCE X-API-Key: lup_{workspace}_{builder}_{secret}
The enrichment contract
Enriched prompts carry domain context in an exact, machine-parseable delimiter block. If nothing matches, your prompt passes through untouched with objects_applied: [] and low confidence — Levelupp never pads, never invents.
{ "enriched_prompt": "<your prompt> ---LEVELUPP EXPERT CORE--- [certified domain context] ---END LEVELUPP EXPERT CORE---", "objects_applied": ["rule_017", "edge_case_006"], "confidence": "high" }
Nine MCP tools across enrichment, expert sessions, and Validated AIDLC.
The flagship. Matches a prompt against your certified knowledge and returns it enriched with the Expert Core block, applied object IDs, and a confidence rating.
Ask the Expert Core a direct domain question — including stage-aware Validated AIDLC guidance — without wrapping it in a build prompt.
Browse the certified knowledge available to your workspace: shared baseline plus your private overrides and additions.
Spin up a knowledge-capture session against a Business Objective straight from your coding agent.
Pull the accumulated context of an existing session into your current conversation.
Persist what your agent learned back to the session — context survives across conversations and machines.
Where is this project in the lifecycle? Registration state, stage, riders, and what's next.
Fetch the versioned governance artifacts written into your repo — the CODEOWNERS gate and CI eval gate.
Summarise a Business Objective: participants, sessions, and the knowledge produced against it.
The Model Context Protocol is an open standard (originated by Anthropic, now Linux Foundation infrastructure) that lets AI assistants call external tools and data sources. Levelupp implements it over streamable HTTP, so clients like Claude Code and Claude Desktop can pull certified domain knowledge into a conversation automatically — no plugins, no copy-paste.
No. Enrichment is keyword-matched against a pre-merged in-memory index — typically ~100ms, not an LLM round-trip. If nothing matches, your prompt passes through unchanged.
A builder key (issued by your workspace admin) or a builder login for the OAuth flow, plus the three-line MCP config above. Setup is around 30 seconds.
Anything that speaks MCP over streamable HTTP: Claude Code, Claude Desktop (as a custom connector with OAuth), and any other MCP-compatible client using the X-API-Key header.
The tool descriptions instruct the model to call Levelupp before responding to prompts that touch your domain — the areas your certified knowledge covers. Outside those areas, your prompts are untouched.
From you. Levelupp reads what your tools already reach and adds its own research to work out what needs validating; your domain experts certify it, and only certified objects are ever served. The full governance story — certification, workspace isolation, Validated AIDLC, provenance — is on the Levelupp product page.
Levelupp MCP comes with a Levelupp workspace. Request access for your team, or read about the platform behind the server.