OKF Knowledge Agent MCP Server
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@OKF Knowledge Agent MCP ServerQuery knowledge about machine learning"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
OKF Knowledge Agent
An LLM-managed knowledge base following the Open Knowledge Format (OKF) v0.1 spec — a bundle of plain markdown files with YAML frontmatter, readable by humans, diffable in git, managed by an agent.
Three ways in, one agent:
MCP server —
kb_query/kb_add/kb_update/kb_statustools over stdio or streamable HTTP. Each call drives an internal LLM agent with the OKF spec in its system prompt.Web UI — browse the bundle (tree, concept viewer, update log, conformance badge) and chat with the same agent to test it. Tool calls render inline so you can watch it work.
CLI —
pnpm agent:query "..."/pnpm agent:mutate "..."smoke entries.
Design rule: conformance is enforced in code, not prompts. The deterministic bundle layer validates frontmatter (type required), regenerates index.md files, appends log.md entries (newest-first, spec §7), and sandboxes all paths to the bundle root. The LLM decides what to change; the code guarantees the result is a conformant bundle.
Stack
pnpm monorepo:
Package | What |
| OKF bundle layer (zero LLM) + agent (Vercel AI SDK tool loop: search/read/list/write/patch/delete) + provider registry |
| Fastify: MCP streamable-HTTP at |
| Vite + React + TS + Tailwind: bundle browser + agent chat ( |
Providers (env-selected, swappable per chat): Anthropic (default), OpenRouter, llamacpp (llama.cpp llama-server / llama-swap — model auto-discovered from /v1/models, loaded model preferred), local (any other OpenAI-compatible endpoint).
llama.cpp
# on the inference box — --jinja enables OpenAI-style tool calling
llama-server -m model.gguf --jinja --host 0.0.0.0 --port 8080
# here — no model id needed, it's discovered
LLM_PROVIDER=llamacpp LLAMACPP_BASE_URL=http://inference-box:8080 \
BUNDLE_ROOT=./sample-bundle node packages/server/dist/index.jsWorks behind llama-swap too: discovery prefers the currently loaded model so a query doesn't trigger a multi-minute model swap. Pin a specific model with LLM_MODEL=.
Related MCP server: Kremis
Quick start
pnpm install
pnpm build
cp .env.example .env # add your API key
BUNDLE_ROOT=./sample-bundle ANTHROPIC_API_KEY=sk-... node packages/server/dist/index.js
# → http://localhost:3800 (web UI + /api + /mcp)Dev mode (server on :3800, Vite HMR on :5180 with proxy):
BUNDLE_ROOT=./sample-bundle pnpm --filter @okf-agent/server dev
pnpm --filter @okf-agent/web devMCP registration (Claude Code / Desktop)
claude mcp add okf-kb \
-e BUNDLE_ROOT=/path/to/your/bundle \
-e ANTHROPIC_API_KEY=sk-... \
-- node /path/to/okf-agent/packages/server/dist/mcp/stdio.jsOr point an HTTP MCP client at http://host:3800/mcp.
Docker
docker compose up --build
# bundle is a volume mount — point ./sample-bundle at any OKF bundleTests
pnpm test # core: 15 tests (spec §5/§6/§7/§9, sandbox, search, concurrency)
pnpm --filter @okf-agent/server exec tsx scripts/mcp-smoke.mts # MCP stdio round-trip (needs SMOKE_BUNDLE + an API key)Environment
See .env.example. BUNDLE_ROOT is required; GIT_AUTOCOMMIT=true commits every mutation.
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