LLM Wiki
Enables using OpenAI-compatible APIs for generating embeddings to enable semantic search in the wiki.
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., "@LLM Wikisearch the wiki for authentication flow"
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.
LLM Wiki
@autocut-cli/llm-wiki builds a local, citation-aware wiki from an explicitly
approved project scope. It can be used directly or by any MCP client, including
AutoCut, Claude Code, Codex, and Hermes.
Public surface
CLI:
llm-wikiMCP server:
llm-wiki serve --root <project>MCP transport: stdio
MCP tools:
wiki_exploreonlyRuntime: Node.js 24 or newer
The management CLI owns initialization, building, provider profiles, and structured knowledge updates. Agents querying over MCP cannot mutate the wiki.
Related MCP server: personal-llm-wiki-kit
Quick start
npm install --global @autocut-cli/llm-wiki
llm-wiki catalog --root /path/to/project --json
llm-wiki init --root /path/to/project --select README.md --yes --json
llm-wiki provider set wiki-generation \
--kind anthropic --model YOUR_MODEL_ID
llm-wiki provider set-key wiki-generation --key-stdin
llm-wiki provider use wiki-generation --root /path/to/project
llm-wiki build --root /path/to/project --json
llm-wiki serve --root /path/to/projectprovider set-key accepts the credential only on stdin, never in process
arguments. The default keyring profile persists until a project selects a
different profile. For headless environments, use
--credential-store env --env-name YOUR_VARIABLE when creating the profile
instead.
init shows only eligible first-level entries and defaults all of them to
selected. Selected directories are traversed recursively. Any path segment that
starts with . and every Git-ignored file are excluded.
If Git metadata is present but Git cannot verify the repository scope,
cataloging, status verification, and builds fail closed with
GIT_SCOPE_UNAVAILABLE; they never fall back to broader filesystem traversal.
Consent also records whether Git or filesystem filtering was confirmed. If that
strategy later changes, source enumeration stops with SOURCE_SCOPE_CHANGED
until the user re-runs init. State created before this field existed must
likewise be reconfirmed once (SOURCE_SCOPE_RECONFIRM_REQUIRED).
If a build process is interrupted, the next status check reclaims its
dead-owner lock and reports BUILD_INTERRUPTED, so rebuilding can resume
automatically. Lock recovery is serialized with a cross-platform process lock,
including recovery from a process that exits during the recovery operation.
Interactive init uses a first-level checklist: Up/Down moves, Space toggles,
Enter confirms, and Escape cancels. Non-interactive callers must pass both
--yes and one or more explicit --select values.
Local files
The only project file intended for commit is llm-wiki.json. Local consent,
credentials references, build state, source proxies, and immutable generations
live under .llm-wiki/. In Git projects, init adds /.llm-wiki/ to the
repository-local .git/info/exclude; it does not edit the shared .gitignore.
Provider secrets are never written to either location. They are read from a system credential store or an explicitly named environment variable.
Compiler adapter
Production builds use an exact-pinned reviewed llm-wiki-compiler fork.
It adds native compile({ embeddings: false, systemPolicy }) support and source
deletion reconciliation. Tests inject a deterministic engine.
Semantic retrieval is off by default. When enabled, it uses a private SQLite derived cache over compiled Wiki pages only; raw source proxies are never the search corpus. Completed page batches are committed immediately, so a later provider failure or cancelled build can resume without resending completed pages. The embedding client supports OpenAI-compatible and Voyage endpoints.
During an incremental build, the remote embedding provider may receive a strictly length-bounded query containing the topic, source locator, and a short new-evidence excerpt from the user-confirmed source scope. This query is used only to recall existing compiled pages and is not added to the searchable corpus. No automatic secret-pattern redaction is claimed: enabling semantic retrieval authorizes this bounded query egress to the selected independent provider.
Semantic mode requires an explicit embedding profile whose name and credential both differ from the Wiki generation profile and credential. The generation key is never passed to the embedding client. A successful build records only the embedding profile, provider kind, model, availability, and a reason code in its manifest—never a credential.
llm-wiki provider set wiki-generation \
--kind openai-compatible --model generation-model \
--credential-store env --env-name WIKI_GENERATION_KEY
llm-wiki provider set wiki-embedding \
--kind voyage --model voyage-3 \
--credential-store env --env-name WIKI_EMBEDDING_KEY
llm-wiki provider use wiki-generation --root /project
llm-wiki provider use-embedding wiki-embedding --root /project
llm-wiki semantic enable --root /project
llm-wiki build --root /projectAt build and query time, a missing or changed embedding profile, missing credential, bad index, or provider failure produces a stable semantic reason code and falls back to lexical retrieval from compiled Wiki pages in the last good generation.
serve is strictly read-only and exits with its stdio client. Automatic builds
run only under the explicit llm-wiki watch --root <project> process; a query
never starts a build.
status verifies the approved source scope by default. Polling integrations can
use status --fast to read the committed generation and runtime state without
rescanning or hashing project files; their watcher remains responsible for
marking source changes stale.
Client registration
llm-wiki install and llm-wiki uninstall delegate registration to the
installed Claude Code, Codex, and Hermes CLIs. They do not edit those clients'
configuration files directly. Missing clients produce stable reason codes;
Hermes keeps its required interactive discovery flow.
Management JSON contract
With --json, stdout is exactly one JSON envelope:
{"ok":true,"command":"status","data":{}}Failures use:
{"ok":false,"command":"build","error":{"code":"ERROR_CODE","message":"..."}}Structured knowledge never travels in process arguments:
printf '%s' '{"id":"decision-1","title":"Decision","text":"Use stdio."}' |
llm-wiki upsert --root /project --jsondelete likewise reads {"id":"decision-1"} from stdin.
This server cannot be installed
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Related MCP Servers
- Flicense-qualityDmaintenanceAn MCP server for Wiki.js projects that enables full-text search, page retrieval, and page management capabilities. It allows LLMs to interact with wiki content through specialized tools for searching, listing, and creating pages.Last updated
- Flicense-qualityCmaintenanceEnables querying a local wiki through MCP-style tools, including search, Q\&A, and knowledge map, with a web viewer for human browsing.Last updated
- Alicense-qualityBmaintenanceAn MCP server that ingests books into a structured, cross-linked wiki of sources, entities, concepts, and syntheses, managed by an LLM.Last updated381MIT
- Alicense-qualityBmaintenanceTurns a git-backed markdown directory into an MCP-compatible knowledge server, enabling any MCP client to read, search, ingest, and maintain a persistent wiki that compounds across sessions.Last updatedMIT
Related MCP Connectors
Agent-native MCP server over the public saagarpatel.dev corpus. Read-only, stateless.
Self-hostable team wiki; agents read & write it via MCP; Atlas turns your repo into a cited wiki.
Serve a folder of Markdown notes as an MCP server: hybrid search, reading, and sourced answers.
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/TigerOfCountryYao/llm-wiki-mcp'
If you have feedback or need assistance with the MCP directory API, please join our Discord server