Context7
Up-to-date docs for AI agents
제작자가 쓴 설명(영어 원문)
Local-first knowledge vaults for project docs and specs. Tagged, versioned, full-text searchable.
이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.
이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.
쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.
LOREDOCS_PRO비밀로 표시된 값은 내 계정의 열쇠예요. 절대 다른 사람과 공유하거나 채팅에 붙여 넣지 마세요.
필요한 것
어떤 앱을 쓰세요?
위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.
Claude Desktop → Settings → Developer → Edit Config를 열고 claude_desktop_config.json에 이 내용을 붙여 넣으세요
{
"mcpServers": {
"loredocs": {
"command": "uvx",
"args": [
"loredocs"
],
"env": {
"LOREDOCS_PRO": "your-value"
}
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add loredocs --env LOREDOCS_PRO=your-value -- uvx loredocs실행하기 전에 빈 값을 채워 주세요.
프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"loredocs": {
"command": "uvx",
"args": [
"loredocs"
],
"env": {
"LOREDOCS_PRO": "your-value"
}
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"loredocs": {
"type": "stdio",
"command": "uvx",
"args": [
"loredocs"
],
"env": {
"LOREDOCS_PRO": "your-value"
}
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
이 서버는 내 컴퓨터에서 실행되는데, ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요. 다른 앱을 고르세요.
선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.
이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.
내 컴퓨터에서 실행돼요. 설치하면 AI 앱에 도구 목록이 나타나요.
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 6일 점검
레지스트리 이름이 GitHub 계정 labyrinth-analytics 기준으로 확인되었고, 이 계정이 저장소를 소유하고 있어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
내 컴퓨터에서 실행되는 서버라 인터넷 엔드포인트가 없어요
내 컴퓨터에서 실행되며, 대신 로컬 설정을 사용해요
내 컴퓨터에서 실행돼요. 도구 목록은 인터넷 엔드포인트가 있는 서버에서만 읽을 수 있어요
레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.
해당하는 기본 점검 1개 중 1개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.
입력해야 할 값: LOREDOCS_PRO
내 컴퓨터에서 실행돼요. AI 앱이 필요할 때 실행하고, 데이터는 제작자의 서버를 거치지 않아요(서버 자체가 온라인 서비스를 호출하는 경우는 제외).
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(0.1.32)은 8일 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Python (uv)도 있어야 해요.
같은 카테고리에는: Context7, Codebase Memory, Exa
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
Up-to-date docs for AI agents
Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.
Connect AI agents to Exa for web search, content fetching, and multi-step research.
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
Your AI project's knowledge base. Organized, searchable, version-tracked.
LoreDocs gives Claude persistent access to your project documentation -- specs, guides, architecture decisions, reference docs -- so it never loses context between sessions. Works with Claude Code, Cowork, Cursor, OpenAI Codex, and Hermes Agent.
Install directly from Claude Code's plugin marketplace, or via PyPI:
uvx loredocs
Prerequisites: uv (fast Python package manager).
# Install uv: https://docs.astral.sh/uv/getting-started/installation/
cd /path/to/loredocs uv sync
For detailed installation instructions, see INSTALL.md.
Using the Claude Agent SDK directly? git clone the public repo and point the SDK's local-directory plugin loader at it -- the repo root is a self-contained plugin directory (.claude-plugin/plugin.json + .mcp.json). No separate SDK-installable bundle exists or is needed.
claude --plugin-dir /path/to/loredocs
Or inside an existing session:
/plugin add /path/to/loredocs
Once loaded, Claude has access to all 49 LoreDocs MCP tools automatically. Ask Claude to "create a vault for this project" or "find the architecture doc" and it uses the tools on its own.
loredocs source folderShared Database Access: Cowork runs in a sandboxed VM. To access docs saved from Claude Code, ask Claude:
"Mount my ~/.loredocs folder"
For Hermes Agent users, add LoreDocs as an MCP server under mcp_servers: in ~/.hermes/config.yaml (see INSTALL.md for the full entry), then restart Hermes.
All 49 LoreDocs MCP tools are then available in your Hermes sessions.
When using LoreDocs with Hermes Agent:
loredocs version you pin from PyPI via uvx. There is no automatic self-update.~/.loredocs/ in SQLite format. No data is sent to cloud services or external servers.BAAI/bge-small-en-v1.5 embedding model from Hugging Face once, on first use. The optional Notion import calls the Notion API with a token you provide. LoreDocs makes no other network calls.LoreDocs organizes knowledge into vaults -- named containers for related documents. Each vault can hold specs, guides, decisions, checklists, or any text you want Claude to remember.
~/.loredocs/loredocs.db <-- SQLite database (metadata, search index)
~/.loredocs/vaults/ / <-- Document files on disk
Key concepts:
LoreDocs works through MCP tools when they are available and falls back to bundled scripts automatically when they are not. Your vault documents are safe regardless of MCP status -- the same add, search, and retrieve operations work either way. You do not need to configure anything; the plugin skill handles the switch silently.
After installing, verify LoreDocs is working by asking Claude:
"Run
vault_listand show me the results."
If you see a list of vaults (or an empty list if this is your first time), LoreDocs is connected. If you get an error about missing tools, re-run uv sync and reload the plugin.
For the best experience, add the following snippet to your ~/.claude/CLAUDE.md (global) or your project's CLAUDE.md. This tells Claude how to use LoreDocs consistently across sessions.
## LoreDocs (persistent project knowledge)
At session start:
vault_list to see available knowledge vaults.vault_inject_summary for any vaults relevant to the current project.During the session:
vault_add_doc.vault_tag_doc.At session end:
For Cowork users: Cowork does not run hooks automatically. Add instructions to call vault_list and vault_inject_summary at session start in your project CLAUDE.md.
In multi-agent environments, different tools and agents often create improvised mirrors of shared skill or configuration content -- playbooks, style guides, shared reference docs. Those mirrors drift. One agent updates the source; the other keeps reading the stale copy. Two agents in the same project end up operating from divergent knowledge with no visible signal that anything is wrong.
LoreDocs prevents this by making the vault the single canonical source that every agent reads. Instead of each agent loading a local file copy, every agent calls vault_inject_by_tag at session start and gets the same vault-managed version.
Store shared content (playbooks, team guidelines, shared specs) as vault documents rather than as local files that agents copy or mirror.
Agents load the content at session start:
vault_inject_by_tag: team-playbook
All agents -- regardless of surface (Claude Code, Cowork, CLI, or any future AI tool) -- call the same vault and receive the same current version. Updating the content requires editing the vault document once; all agents pick up the change on their next session start.
Local files (.claude/skills/, .agents/, or any surface-specific config) become pointers or bootstrap stubs only -- not the authoritative content. The vault is the source of truth.
# Session start for any agent on the team:
vault_inject_by_tag("team-playbook")
vault_inject_by_tag("project-architecture")
To store the shared content in the vault (one time, or on each update):
# Store (or update) the shared playbook:
vault_update_doc(vault="team-knowledge", doc_id="playbook-id", content=open("PLAYBOOK.md").read())
vault_add_doc(vault="team-knowledge", name="Team Playbook", path="/absolute/path/to/PLAYBOOK.md", tags=["team-playbook"])
Any agent that calls vault_inject_by_tag("team-playbook") reads the same document. No copies, no mirrors, no drift.
LoreDocs is local-first and free to use. Pro ($9/mo) removes the storage limits and unlocks semantic (meaning-based) retrieval. Everything runs on your machine on either plan -- Pro does not add any cloud component.
| Free | Pro ($9/mo) | |
|---|---|---|
| Vaults | 3 | Unlimited |
| Documents per vault | 50 | Unlimited |
| Storage | 500 MB | Unlimited |
| Version history per document | 5 versions | Unlimited |
| Full-text search (FTS5) | Yes | Yes |
| Core MCP tools (create, search, version, tag, inject, import/export) | Yes | Yes |
| Local-first, no cloud, no telemetry | Yes | Yes |
Semantic search (vault_search semantic=true, vault_rebuild_index) | -- | Yes |
Embedding-based document relationships (vault_find_related) | Keyword co-occurrence only | Keyword + embedding auto-links |
Cross-product session linking (vault_link_session + 2 more) | -- | Yes (also requires LoreConvo Pro) |
After checkout, your license key is emailed automatically to the address you used at checkout, usually within a few minutes. Questions: info@labyrinthanalyticsconsulting.com.
Free tier limits are enforced before writes; Pro removes them. Check your current tier and usage anytime with vault_tier_status. Activate a Pro license with vault_set_tier.
The Pro semantic features use a local embedding model (BGE-small-en-v1.5) and the
LanceDB index -- still no data leaves your machine.
vault_find_related returns both keyword co-occurrence and embedding-based auto-links for Pro users. Uses BGE-small-en-v1.5, cosine >= 0.75, same-vault scoped. Embedding links are archived if you downgrade from Pro to Free.vault_link_session, vault_get_session_links, vault_get_linked_sessions. Requires both LoreDocs Pro and LoreConvo Pro.LoreDocs provides 49 MCP tools by default (50 with the notion extra installed; 51 with LOREDOCS_ENABLE_CAP_TOOLS=1 and the notion extra) organized by function:
| Tool | What it does |
|---|---|
vault_create | Create a new vault with name and description |
vault_list | List all vaults with doc counts and sizes |
vault_info | Get detailed vault information |
vault_archive | Archive a vault (preserves data, hides from listing) |
vault_delete | Permanently delete a vault and all its documents |
vault_link_project | Link a vault to a project directory |
vault_open_workspace | Open or create the vault scoped to a directory path |
loredocs_onboard | Set up workspace with starter vaults on first install |
| Tool | What it does |
|---|---|
vault_add_doc | Add a new document to a vault (inline content or from file path) |
vault_update_doc | Update document content (creates version history) |
vault_remove_doc | Remove a document from a vault |
vault_get_doc | Retrieve a document with full content |
vault_list_docs | List documents in a vault with filtering and sorting |
vault_copy_doc | Copy a document to another vault |
vault_move_doc | Move a document to another vault |
vault_doc_history | View version history of a document |
vault_doc_restore | Restore a document to a previous version |
| Tool | What it does |
|---|---|
vault_search | Full-text search across all vaults |
vault_search_by_tag | Find documents by tag across all vaults |
| vault_find_related | Discover documents related to a given doc (Pro
앞부분만 보여 드려요. 나머지는 저장소에서 읽어 보세요