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Aurekai MCP

  • Updated May 3, 2026
  • aurekai/aurekai-mcp

Aurekai MCP is a MCP server that exposes akai doctor, manifests, artifacts, feature queries, and runtime inspection to your agent.

About

The Aurekai MCP server connects AI coding agents to the Aurekai akai stack through Model Context Protocol stdio transport. Developers who run Aurekai-powered agents install it when they need doctor-style diagnostics, manifest and artifact lookups, feature queries, and runtime inspection from the same session where they edit code. It is aimed at operators and developers already on Aurekai who want fewer context switches than opening separate dashboards or CLI-only flows. Use it during build when integrating Aurekai, and keep it registered in operate when you iterate on live behavior or debug odd runtime states. The package publishes as @aurekai/mcp on npm with server schema version 0.8.0-alpha.3, so expect alpha APIs and verify behavior before relying on it in critical paths. It complements agent skills by offering protocol-level tools rather than prompt recipes.

  • akai doctor diagnostics exposed as MCP tools for agent-driven health checks
  • Query manifests and artifacts without leaving the coding agent
  • Feature-query and runtime inspection for Aurekai-based workflows
  • stdio transport via @aurekai/mcp npm package (v0.8.0-alpha.3)
  • GitHub source: aurekai/aurekai-mcp for self-hosted stdio wiring

Aurekai MCP by the numbers

  • Data as of Aug 10, 2026 (Skillselion catalog sync)
terminal
claude mcp add aurekai-mcp -- npx -y @aurekai/mcp

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Package@aurekai/mcp
TransportSTDIO
AuthNone
Last updatedMay 3, 2026
Repositoryaurekai/aurekai-mcp

What it does

Wire Claude Code or Cursor to Aurekai akai doctor, manifests, artifacts, and live runtime checks while you ship agent features.

Who is it for?

Best when you're shipping Aurekai or akai-based agents and want in-editor diagnostics and artifact visibility.

Skip if: Skip if you're not using Aurekai and only need generic log tailing or unrelated cloud monitoring.

What you get

Your agent can run doctor checks, query features, and inspect runtime state through stdio MCP tools aligned with your Aurekai workflow.

  • MCP tools for doctor, manifests, artifacts, and feature queries
  • Agent-callable runtime inspection without custom glue code

By the numbers

  • Server version 0.8.0-alpha.3
  • Single npm package @aurekai/mcp with stdio transport
  • Repository: github.com/aurekai/aurekai-mcp
README.md

Aurekai

@aurekai/mcp — Aurekai MCP Server

0.8.0-alpha.5 · capability-native · zero dependencies · stdio + Streamable HTTP

Exposes all 9 Aurekai capability families (111 commands) as MCP tools with full protocol-level features: tool annotations, resource pagination, named prompts, _meta proof propagation, and embedded resource outputs.

Install

npm install -g @aurekai/mcp

Usage

stdio (default — for Claude Desktop, Cursor, etc.)

// claude_desktop_config.json
{
  "mcpServers": {
    "aurekai": {
      "command": "aurekai-mcp"
    }
  }
}

Streamable HTTP (optional)

AKAI_MCP_HTTP_PORT=3100 aurekai-mcp
# POST JSON-RPC to http://127.0.0.1:3100/mcp

Protocol Surface

Feature Status
tools/list — 89 operators across 9 capability families
Tool annotations (readOnlyHint, destructiveHint, idempotentHint)
resources/list — 13 aurekai:// resource URIs
resources/read — live reads for runtime/capabilities, queue/stats, models
Resource pagination (nextCursor)
Resource subscriptions (acknowledge)
prompts/list + prompts/get — 8 named capability prompts
_meta proof propagation on tool call results
Embedded resource outputs for proof-emitting tools
logging server capability
Streamable HTTP transport (AKAI_MCP_HTTP_PORT)

Capability Families

Family Operators Examples
runtime 11 akai_api, akai_queue, akai_workflow
commerce 11 akai_gate, akai_pay, akai_ledger
intake 12 akai_transcribe, akai_ingest, akai_segment
memory 11 akai_fpq, akai_fpqx, akai_embed, akai_vec
proof 8 akai_proof, akai_canon, akai_graph, akai_hash
reason 5 akai_reason, akai_physics, akai_flow, akai_learn
wire 5 akai_tel, akai_wire, akai_moq, akai_net
publish 9 akai_brief, akai_narrate, akai_pack, akai_distribute
substrate 17 akai_capability, akai_space, akai_compress

Named Prompts

Prompt Description
turn-this-call-into-a-deliverable audio → transcribe → brief → deliverable
inspect-this-artifact-lineage Resolve full Merkle lineage for an artifact
build-a-model-memory-pack FPQ compress + roundtrip + export memory pack
compare-these-reasoning-branches Dual branch diff with recommendation
generate-client-invoice-from-usage Metering records → invoice
produce-wire-device-report PCAP → SIP event + device report
run-a-release-gate proof validate + manifest verify + SLI auto-run
make-a-client-brief-from-this-audio audio → transcript → structured client brief

Resources (aurekai:// URIs)

aurekai://runtime/capabilities · aurekai://queue/stats · aurekai://ledger/portfolio aurekai://models · aurekai://model-memory · aurekai://features/{artifact} aurekai://proof/{id} · aurekai://graph/{node}/lineage · aurekai://space/{name} aurekai://wire/{capture_id} · aurekai://project/{id} · aurekai://invoice/{id} · aurekai://cms/{entry_id}

Runtime Requirement

Tools require the akai binary on PATH (from aurekai/native-runtime) or set AKAI_BIN=/path/to/akai. Without it, tools return a clear error message — no crash.

Registry Targets

Recommended MCP Servers

How it compares

MCP integration for the Aurekai runtime, not a standalone agent skill or generic observability SaaS.

FAQ

Who is Aurekai MCP for?

Developers and small teams building on Aurekai who want MCP tools for doctor, manifests, artifacts, and runtime inspection inside their coding agent.

When should I use Aurekai MCP?

Use it when you are debugging Aurekai features, validating manifests or artifacts, or inspecting runtime behavior during build and operate iterations.

How do I add Aurekai MCP to my agent?

Register the stdio server using the @aurekai/mcp npm package in your agent’s MCP config, pointing at the published version and restarting the client.

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