mcp-aurekai
Aurekai MCP exposes 89 native akai_\* runtime operators to any MCP-compatible host, covering the full Aurekai binary family — API gateway, artifact inspection, proof bundle export, semantic embedding, batch queuing, entity detection, compression, and more. Zero external dependencies; runs locally via npx -y @aurekai/mcp.
README
<p align="center"> <img src="https://raw.githubusercontent.com/aurekai/aurekai/main/assets/aurekai-logo.svg" alt="Aurekai" width="520" /> </p>
@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
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.