Obsidian Wrapper
БесплатноНе проверенEnables Claude Desktop to securely search and retrieve knowledge from an Obsidian vault through a stateless MCP interface, with progressive disclosure and gated
Описание
Enables Claude Desktop to securely search and retrieve knowledge from an Obsidian vault through a stateless MCP interface, with progressive disclosure and gated write capabilities.
README
Obsidian MCP Wrapper is a session-stateless MCP retrieval system for an agency Obsidian vault. It gives Claude Desktop users controlled access to indexed Markdown knowledge without giving the model direct, unbounded filesystem access or unsupervised write privileges.
The runtime has two layers:
pf-mcp: a lightweight STDIO MCP shim that runs on each Claude Desktop workstation.pf-index: a shared LAN/VPN retrieval service that owns the vault index, signed handles, bearer-token authentication, rate limits, write locking, and the audit log.
The design goal is progressive disclosure: search returns compact snippets and signed section handles first, then Claude expands only the context it needs.
Highlights
- Standard-library core runtime for the default HTTP server path.
- Optional FastAPI/uvicorn ASGI boundary.
- SQLite FTS5 lexical search over immutable vault index epochs.
- HMAC-signed section handles that resolve against retained snapshots.
- Manifest-only filesystem access for indexed Markdown paths.
- Human-gated append writes into client, provider, carrier, and operational notes.
- Autonomous AI notes routed to a rotated capture inbox by default.
- File locking and SQLite audit records for write operations.
- Sanitized error envelopes that avoid leaking paths, tokens, URLs, or tracebacks into Claude.
- Quick-start, deployment, teardown, and nightly-refresh scripts.
Runtime Topology
Claude Desktop
-> STDIO MCP JSON-RPC
-> pf-mcp workstation shim
-> HTTP POST /tools/<tool_name>
-> pf-index LAN/VPN service
-> Obsidian_Vault Markdown snapshots and .pf_index artifacts
pf-index consumes Markdown and derived index artifacts. It does not need the
source DuckDB database at runtime.
Repository Layout
.
|-- Docs/
| |-- ARCHITECTURE.md
| |-- DEPLOYMENT.md
| |-- QUICKSTART.md
| `-- MCP_WRAPPER_MASTER_PROMPT.md
|-- config/
| |-- claude_desktop_config.example.json
| |-- deployment_manifest.example.json
| |-- pf-index.example.toml
| `-- pf-mcp.env.example
|-- pf_index/
| |-- api/ HTTP boundaries
| |-- core/ indexing, retrieval, crypto, paths, writes
| `-- config.py TOML and environment configuration
|-- pf_mcp/
| `-- main.py STDIO MCP shim
|-- scripts/
| |-- build_index.py
| |-- run_pf_index.py
| |-- quickstart.sh
| |-- quickstart_teardown.sh
| |-- nightly_refresh.sh
| |-- deploy_interactive.sh
| `-- deploy_teardown.sh
|-- tests/
|-- pyproject.toml
`-- requirements.lock
MCP Tools
The shim exposes these tools to Claude:
| Tool | Purpose |
|---|---|
vault_search |
Search indexed vault sections and return snippets with signed handles. |
strategy_search |
Search strategy, advisory, sales, renewal, and operating-system material. |
find_note |
Find likely note paths by query. |
get_note_summary |
Return a bounded summary/outline for one note path. |
get_entity_context |
Entity-oriented search wrapper. |
search_tables |
Search indexed table-like content. |
read_section |
Resolve one signed handle into a larger section excerpt. |
expand_context |
Resolve several signed handles within a token budget. |
get_full_profile |
Retrieve full materialized context for one known client or provider. |
advisory_context |
Combine profile evidence with strategy context for planning questions. |
vault_stats |
Return index and vault statistics. |
append_human_note |
Append a factual note through the gated write pipeline. |
remove_note |
Remove a specific generated note entry by note id. |
Security Model
Important boundaries:
- The MCP shim validates argument shapes and hard limits before forwarding to the LAN service.
- The LAN service requires
Authorization: Bearer <token>. - Tokens map to user ids for audit and idempotency.
- Runtime reads are limited to paths listed in the active index manifest.
- Path validation rejects absolute paths, traversal, null bytes, URL schemes, Windows drive paths, and backslash paths.
- Section handles contain path, line range, content hash, file hash, vault id, and index epoch, then are signed with HMAC-SHA256.
- Old handles resolve against retained immutable snapshots, not changed live vault files.
- Autonomous writes are redirected to the configured capture inbox unless the human explicitly directs a write to a specific note.
- Write operations are append-only/gated, locked, audited, and bounded by configured note length limits.
Requirements
- Python 3.11 or newer
- Markdown Obsidian vault directory
- HMAC secret for handle signing
- One or more bearer tokens for users
The default pf_index.api.server HTTP boundary uses only the Python standard
library. Optional FastAPI dependencies are listed in requirements.lock:
python -m pip install -r requirements.lock
Quick Start
For a complete local smoke test, use the maintained guide:
sed -n '1,240p' Docs/QUICKSTART.md
The short version:
export PF_APP_DIR="$PWD"
export PF_DEMO_ROOT=/tmp/pf-mcp-demo
export PF_VAULT_ROOT="$PF_DEMO_ROOT/Obsidian_Vault"
export PF_INDEX_ROOT="$PF_DEMO_ROOT/.pf_index"
export PF_AUDIT_DB="$PF_INDEX_ROOT/write_audit.sqlite"
export PF_INDEX_HMAC_SECRET="local-demo-secret-change-me"
export PF_INDEX_TOKEN="local-demo-token"
export PF_INDEX_CONFIG="$PF_DEMO_ROOT/pf-index.toml"
Create a small test vault and config as shown in Docs/QUICKSTART.md, then
build an index:
PYTHONPATH="$PF_APP_DIR" python -m scripts.build_index \
--config "$PF_INDEX_CONFIG" \
--epoch 2026-06-08T120000Z
Run the stdlib HTTP server:
PYTHONPATH="$PF_APP_DIR" \
PF_INDEX_HMAC_SECRET="$PF_INDEX_HMAC_SECRET" \
python -m pf_index.api.server \
--host 127.0.0.1 \
--port 8765 \
--config "$PF_INDEX_CONFIG"
Search through the API:
curl -s \
-H "Authorization: Bearer $PF_INDEX_TOKEN" \
-H "Content-Type: application/json" \
-d '{"query":"Coverage","max_results":3,"max_tokens":1000}' \
http://127.0.0.1:8765/tools/vault_search \
| python -m json.tool
List MCP tools through the shim:
printf '%s\n' '{"jsonrpc":"2.0","id":1,"method":"tools/list","params":{}}' \
| PYTHONPATH="$PF_APP_DIR" \
PF_INDEX_URL="http://127.0.0.1:8765" \
PF_INDEX_TOKEN="$PF_INDEX_TOKEN" \
python -m pf_mcp.main \
| python -m json.tool
Or run the automated path:
bash scripts/quickstart.sh
Tear down demo artifacts:
bash scripts/quickstart_teardown.sh
Configuration
Server-side config lives in TOML. Start from:
cp config/pf-index.example.toml pf-index.toml
Key sections:
[paths]:vault_root,index_root, andaudit_db[limits]: result, token, note length, lock timeout, and concurrency limits[security]:vault_idand HMAC secret source[tokens]: bearer token to user id map[inbox]: rotated inbox path for autonomous captures[retention]: retained immutable index epochs
Workstation shim config is environment-based. Start from:
cp config/pf-mcp.env.example pf-mcp.env
Claude Desktop config example:
cat config/claude_desktop_config.example.json
Indexing
Build an immutable index epoch:
PYTHONPATH="$PWD" python -m scripts.build_index --config /path/to/pf-index.toml
Each epoch contains:
.pf_index/builds/<epoch>/
|-- manifest.json
|-- lexical.sqlite
`-- content/<sha256-of-relative-path>.md
The active epoch is selected through .pf_index/ACTIVE. Rolling back is a
controlled edit of that pointer to a retained epoch.
Running The Service
Default stdlib server:
PYTHONPATH="$PWD" python -m pf_index.api.server \
--host 127.0.0.1 \
--port 8765 \
--config /path/to/pf-index.toml
Optional FastAPI boundary:
python -m pip install -r requirements.lock
PYTHONPATH="$PWD" uvicorn pf_index.api.fastapi_app:create_app --factory \
--host 127.0.0.1 \
--port 8765
Testing
Run acceptance and structure tests:
PYTHONDONTWRITEBYTECODE=1 python -m unittest discover -s tests -v
The tests focus on safety contracts such as path validation, signed handles, indexing behavior, write routing, and repository structure.
Deployment
Use Docs/DEPLOYMENT.md for the production runbook. It covers:
- Dedicated service user and filesystem permissions
- Code and vault placement
- HMAC secret generation
- User token generation
- Index build and startup checks
systemdservice setup- LAN/VPN binding and firewall posture
- Runtime egress denial
- Token rotation
- Audit recovery
- Rollback
scripts/deploy_interactive.sh and scripts/deploy_teardown.sh support guided
deployment and cleanup flows.
Nightly Refresh
scripts/nightly_refresh.sh supports a scheduled flow:
sync or refresh source data
-> optionally rebuild Markdown vault from DuckDB
-> build a new immutable index epoch
-> atomically update ACTIVE
If DuckDB-to-Markdown generation happens elsewhere, omit PF_SOURCE_DATABASE
and rebuild the index from the current vault.
Data Boundary
Do not commit or deploy local data artifacts:
agency_core.duckdb- Generated
Obsidian_Vault/ .pf_index/builds.obsidian/.vault_salt- Real
.envfiles - Audit databases
- Exported CSVs, spreadsheets, or reports
The repository is meant to contain application code, tests, docs, and placeholder configuration only.
Further Reading
Docs/ARCHITECTURE.mdfor the full design and safety modelDocs/QUICKSTART.mdfor local smoke testingDocs/DEPLOYMENT.mdfor production operationsDocs/MCP_WRAPPER_MASTER_PROMPT.mdfor operator-facing MCP usage guidance
Установка Obsidian Wrapper
У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.
▸ github.com/UwUGreed/obsidian-mcp-wrapperFAQ
Obsidian Wrapper MCP бесплатный?
Да, Obsidian Wrapper MCP бесплатный — установка в пару кликов через Unyly без оплаты.
Нужен ли API-ключ для Obsidian Wrapper?
Нет, Obsidian Wrapper работает без API-ключей и переменных окружения.
Obsidian Wrapper — hosted или self-hosted?
Self-hosted: сервер запускается локально на твоей машине командой из раздела установки.
Как установить Obsidian Wrapper в Claude Desktop, Claude Code или Cursor?
Открой Obsidian Wrapper на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.
Похожие MCP
Fetch
Web content fetching and conversion for efficient LLM usage.
AWS KB Retrieval
Retrieval from AWS Knowledge Base using Bedrock Agent Runtime.
автор: modelcontextprotocolSpring AI MCP Server
Provides auto-configuration for setting up an MCP server in Spring Boot applications.
llm-analysis-assistant
A very streamlined mcp client that supports calling and monitoring stdio/sse/streamableHttp, and can also view request responses through the /logs page. It also
автор: xuzexin-hzCompare Obsidian Wrapper with
Не уверен что выбрать?
Найди свой стек за 60 секунд
Автор?
Embed-бейдж для README
Похожее
Все в категории ai
