KAIROS MCP

KAIROS MCP is a TypeScript service for storing and executing reusable protocol chains for AI agents. It exposes:

• an MCP endpoint at POST /mcp
• REST endpoints under /api/*
• a browser UI under /ui
• a CLI named kairos

Without persistent workflows, agents repeat work, lose context, and cannot follow multi-step procedures reliably. KAIROS fixes this with three core ideas (the diagrams below list every MCP tool):

• Persistent memory — store and retrieve protocol chains across sessions
• Deterministic execution — activate → forward (per layer) → reward; the server drives next_action at every step
• Agent-facing design — tool descriptions and error messages built for programmatic consumption and recovery

Protocol execution runs in a fixed order: activate (match adapters), forward (run each layer’s contract; loop), then reward (finalize the run). Use train / tune / export / delete / spaces as described in each tool’s MCP description.

Default run order — activate → forward (loop per layer) → reward:

flowchart LR
  A([activate]) --> B([forward])
  B -.-> B
  B --> D([reward])
  style A fill:#4a6fa5,stroke:#2d4a7a,color:#fff
  style B fill:#ffb74d,stroke:#f57c00,color:#333
  style D fill:#81c784,stroke:#388e3c,color:#333

Discovery and adapter lifecycle — no fixed order; follow each tool’s MCP description:

flowchart LR
  S([spaces]) --- TR([train]) --- TU([tune]) --- EX([export]) --- DL([delete])
  style S fill:#4a6fa5,stroke:#2d4a7a,color:#fff
  style TR fill:#ede7f6,stroke:#5e35b1,color:#333
  style TU fill:#fff3e0,stroke:#f57c00,color:#333
  style EX fill:#e8f5e9,stroke:#388e3c,color:#333
  style DL fill:#ffebee,stroke:#c62828,color:#333

The server generates challenge data (nonce, proof_hash, URIs); agents echo those values back exactly.

Protocol execution

Authoritative behavior for agents is defined in the MCP tool resources under src/embed-docs/tools/ (activate, forward, reward). This is an on-wire summary; follow each response’s next_action and must_obey fields in real runs.

1. activate — Provide a short query string (about 3-8 words) on every call. From choices, pick one row and obey that row’s next_action (do not mix in another URI). Typical roles: match (continue with forward on the given adapter URI), refine, create (register a new adapter with train).

2. forward — With the adapter URI from activate, call forward and omit solution on the first call for that run. Read contract and next_action. For each layer, call forward again using the layer URI from the last response (add ?execution_id=... when the server returns it) and supply a solution whose type matches contract.type. Loop until next_action tells you to call reward.

3. reward — After the last layer, call reward with the layer URI from forward (not the adapter URI unless the schema explicitly allows it), outcome (success or failure), and optional evaluator fields per the tool description.

Must always: Obey next_action verbatim. Echo server-issued nonce, proof_hash, and URIs exactly.

Must never: Invent URIs; skip layers; submit a solution whose type does not match contract.type.

For a longer narrative, see the Workflow Engine pages in the KAIROS wiki.

What runs in this repository

The current codebase includes:

• HTTP application server — Express app for MCP, REST, auth routes, and UI
• stdio MCP transport — direct local-host launch path for desktop/IDE MCP clients
• Qdrant-backed adapter store — required for runtime
• Optional Redis cache / proof-of-work state store — enabled when REDIS_URL is set
• Optional Keycloak auth integration — browser session + Bearer JWT validation
• React UI — served from the same origin at /ui
• CLI — talks to the HTTP API

Transport modes

Use one transport mode per process:

kairos serve / kairos-mcp serve (run the MCP server from the npm package):

• --transport stdio|http overrides TRANSPORT_TYPE for that process only.

• If neither is set, serve defaults to stdio (good for local MCP hosts).

• Other kairos commands (login, train, …) do not use --transport; they only see TRANSPORT_TYPE if you set it in the environment (normally leave it unset for CLI-only use).

• TRANSPORT_TYPE=http: serves /mcp, /api/*, /ui, and /health; this is the default for Docker Compose deployments.

• TRANSPORT_TYPE=stdio: runs MCP over stdin/stdout for local hosts such as Claude Desktop, Cursor, or Claude Code. In this mode, stdout is reserved for MCP protocol frames and logs go to stderr.

Quick start

KAIROS runs as a local MCP server that your agent host launches over stdio (the default transport). You do not need to clone this repo or run Docker Compose — install the package globally and point your host at kairos serve.

Prerequisites

• Node.js 24+.

• A Qdrant instance on http://localhost:6333 — KAIROS cannot start without it, and no auth is required for local use. If you don't already run one, this is the quickest option (optional convenience):

  hljs language-bash

  Copy

  docker run -p 6333:6333 qdrant/qdrant
  

• One embedding backend, supplied through the host env below.

Install

npm install -g @debian777/kairos-mcp
kairos --help

The global install provides both the kairos CLI (bulk operations, auth, server management) and the MCP server binary used by your agent host.

Configure your MCP host

Add KAIROS to your host's mcp.json (Cursor, Claude Desktop, Claude Code, …). serve uses stdio by default, so no --transport flag is needed:

{
  "mcpServers": {
    "KAIROS": {
      "command": "kairos",
      "args": ["serve"],
      "env": {
        "QDRANT_URL": "http://localhost:6333",
        "QDRANT_API_KEY": "",
        "OPENAI_API_KEY": "sk-..."
      }
    }
  }
}

QDRANT_API_KEY="" selects no-auth localhost Qdrant. For the embedding backend, supply one of:

• OpenAI — OPENAI_API_KEY
• Ollama / OpenAI-compatible — OPENAI_API_URL, OPENAI_EMBEDDING_MODEL, and OPENAI_API_KEY=ollama
• TEI — TEI_BASE_URL (+ optional TEI_MODEL)

Every parameter is ENV-overridable. To run KAIROS as an HTTP listener instead of stdio, add "--transport", "http" to args (see Transport modes).

Some hosts show a longer agent-visible server id (for example one ending in -KAIROS); see AGENTS.md for the runtime authority note.

When executing over MCP, follow Protocol execution above and each tool result's next_action. The connected server's tool descriptions are the runtime authority if they differ from this file.

Developers: to run the full Docker Compose stack (Qdrant + app + optional Keycloak / Redis / Postgres) for local development and testing, see CONTRIBUTING.md.

CLI

The kairos CLI is installed as part of the global package (see Install above). It provides bulk adapter operations, authentication, export/import, and server management — the same binary your MCP host uses for kairos serve.

kairos --help

See docs/CLI.md.

Add KAIROS to your agent instructions

This repo ships the kairos skill for running protocols. Use --list to see what the skills registry reports for this repo.

If you want agents to use KAIROS consistently, add a short repo rule or instruction such as:

KAIROS MCP is a Model Context Protocol server for persistent memory and deterministic adapter execution. Execute protocols in this order: activate → forward (loop per layer until next_action points to reward) → reward. Echo all server-generated hashes, nonces, and URIs exactly.

Agent skills shipped in this repo

This repository ships its agent skills under .agents/skills/. Two skills are published:

Install the user skill:

npx skills add debian777/kairos-mcp --skill kairos

List available skills:

npx skills add debian777/kairos-mcp --list

Popular global installs:

More detail: .agents/skills/README.md

Helm (advanced)

A Helm chart for Kubernetes deployment lives under helm/. To validate the chart locally (matches the GitHub Actions CI pipeline):

npm run test:helm

See docs/install/helm.md for deployment details.

Documentation map

• Documentation index
• Install and environment
• Cursor and MCP
• CLI reference
• Architecture (KAIROS wiki)
• Adapter examples
• Contributing

Troubleshooting

The server does not start

In stdio mode KAIROS logs to stderr (stdout is reserved for MCP frames). Check your host's MCP log panel for the KAIROS server. The most common cause is Qdrant not being reachable.

KAIROS cannot reach Qdrant

KAIROS requires a Qdrant instance and only becomes healthy once Qdrant is ready. Confirm one is listening on your QDRANT_URL (default http://localhost:6333):

curl http://localhost:6333/readyz

If you run KAIROS in HTTP mode (--transport http), you can also check its own health endpoint (curl http://localhost:3000/health).

Embeddings fail on startup

Set one working embedding backend in the host env:

• OpenAI: OPENAI_API_KEY
• Ollama/OpenAI-compatible: OPENAI_API_URL, OPENAI_EMBEDDING_MODEL, OPENAI_API_KEY=ollama
• TEI: TEI_BASE_URL (+ optional TEI_MODEL)

The CLI keeps asking for login

The CLI stores tokens per API URL. Confirm that:

• you are using the expected --url / KAIROS_API_URL
• the token is still valid
• Keycloak and the KAIROS server agree on issuer and audience

Use:

kairos token --validate

Developers: for Docker Compose, fullstack, and auth troubleshooting, see CONTRIBUTING.md.

Support

• Documentation
• Issues
• Discussions

Trademark

KAIROS MCP™ and the KAIROS MCP logo are trademarks of the project owner. They are not covered by the MIT license. Forks must remove the name and logo.

See TRADEMARK.md.

License

MIT — see LICENSE.