About aurekai-mcp
aurekai-mcp maps Aurekai capability families to MCP tools for developers and agents inspecting runtime state, artifacts, and features. It also provides resources, pagination, and named prompts.
Key features
- 01Covers 9 capability families
- 02Provides 89 operator tools
- 03Reads runtime, queue, and model resources
- 04Supports resource pagination and subscription acknowledgements
- 05Includes 8 named prompts
- 06Propagates proof metadata and embedded resources
Use cases
- 01Inspect Aurekai runtime and queue status
- 02Trace an artifact's Merkle lineage
- 03Turn audio into a brief or deliverable
- 04Validate a release gate and manifest
MCP support
Exposes Aurekai capabilities as MCP tools, resources, and prompts over stdio or Streamable HTTP. Tools require `akai` on PATH or a binary specified through `AKAI_BIN`.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project README
@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
- Smithery
- Glama
- Official MCP Registry
- PulseMCP
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.