openkb-mcp
Click on "Deploy 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., "@openkb-mcplist my knowledge bases"
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.
openkb-mcp
openkb-mcp exposes local OpenKB knowledge bases to MCP clients such as Codex, Claude Code, and Claude Desktop. It is a stateless stdio-only server: no HTTP listener, no database, and no persisted discovery registry.
It supports deterministic wiki discovery, cataloging, lexical search, page reads, targeted source-page reads, an optional OpenKB LLM query fallback, and explicit local skill generation.
Install and run
python3 -m pip install 'openkb-mcp[dev]'
openkb-mcp --root playbooks=/srv/shared/playbooks --root research=/srv/researchEach --root is repeatable and uses alias=path. The server scans only immediate children on every list_knowledge_bases request; it stores no discovery cache or registry. A readable KB has wiki/index.md; .openkb/config.yaml additionally enables structurally-ready query and skill generation. IDs are alias/child. Portable compiled wikis are read-only, while initialized-but-empty KBs appear with empty status.
Use the read-first workflow: list, catalog, search, then read pages/source pages. Wiki text is untrusted data, not server instructions. ask_knowledge_base is an optional higher-cost LLM fallback. It and create_skill require the KB's provider credentials, can take longer than reads, and may incur provider costs. Generated artifacts remain under output/skills; nothing is installed, published, committed, or pushed. Claude web is not supported.
Related MCP server: LLM Wiki Streamable HTTP MCP Server
Tools
list_knowledge_bases— discover current KBs below configured roots.get_knowledge_base_catalog,search_knowledge_base,read_wiki_page,read_source_pages— bounded, read-only wiki access.ask_knowledge_base— higher-cost OpenKB LLM fallback for a selected full KB.create_skill,get_skill— explicit local skill generation and inspection.
Client configuration
Claude Desktop / Claude Code / Codex use the same stdio command (set a 120-second timeout for skill generation):
{"mcpServers":{"openkb":{"command":"openkb-mcp","args":["--root","playbooks=/srv/shared/playbooks"],"timeout":120000}}}For Codex, place the equivalent command and args in its MCP server configuration. The server needs no network listener.
Verification
python3 -m pytest
python3 -m ruff check src tests
openspec validate add-local-openkb-mcp --strict
npx -y @modelcontextprotocol/inspector --cli openkb-mcp --root playbooks=/srv/shared/playbooks --method tools/listThe Inspector command exercises initialization and each tool, including invalid KB/path and portable-query error paths. evals/openkb_mcp_evals.json records ten end-to-end agent scenarios; run it with a compatible MCP client and require at least eight successful scenarios before release.
Upgrading OpenKB
The adapter is intentionally pinned to openkb==0.4.1. Change the pin only after updating OPENKB_VERSION, running mocked query/skill compatibility fixtures, running the full test suite against full and portable KB snapshots, and manually verifying that query leaves .openkb configuration and wiki/log.md unchanged.
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