Xpersona

Crawler Summary

ai-note-searcher-5000 answer-first brief

AI-powered semantic search for Obsidian notes using Qdrant AI Note Searcher 5000 A dockerized semantic search system for Obsidian notes that provides intelligent search capabilities through vector embeddings and an MCP (Model Context Protocol) server for LLM integration. Overview AI Note Searcher 5000 watches your Obsidian notebook folder, creates vector embeddings using Ollama, stores them in Qdrant, and provides semantic search capabilities through an MCP server that LLMs Published capability contract available. No trust telemetry is available yet. 4 GitHub stars reported by the source. Last updated 2/24/2026.

Freshness

Last checked 2/22/2026

Best For

Contract is available with explicit auth and schema references.

Not Ideal For

ai-note-searcher-5000 is not ideal for teams that need stronger public trust telemetry, lower setup complexity, or more explicit contract coverage before production rollout.

Evidence Sources Checked

editorial-content, capability-contract, runtime-metrics, public facts pack

CardFactsSnapshotContractTrust
Claim this agent
Agent DossierGitHubSafety: 80/100

ai-note-searcher-5000

AI-powered semantic search for Obsidian notes using Qdrant AI Note Searcher 5000 A dockerized semantic search system for Obsidian notes that provides intelligent search capabilities through vector embeddings and an MCP (Model Context Protocol) server for LLM integration. Overview AI Note Searcher 5000 watches your Obsidian notebook folder, creates vector embeddings using Ollama, stores them in Qdrant, and provides semantic search capabilities through an MCP server that LLMs

MCPverified

Public facts

7

Change events

1

Artifacts

0

Freshness

Feb 22, 2026

Verifiededitorial-content1 verified compatibility signal4 GitHub stars

Published capability contract available. No trust telemetry is available yet. 4 GitHub stars reported by the source. Last updated 2/24/2026.

4 GitHub starsSchema refs publishedTrust evidence available

Trust score

Unknown

Compatibility

MCP

Freshness

Feb 22, 2026

Vendor

Jarmentor

Artifacts

0

Benchmarks

0

Last release

1.0.0

Executive Summary

Key links, install path, and a quick operational read before the deeper crawl record.

Verifiededitorial-content

Summary

Published capability contract available. No trust telemetry is available yet. 4 GitHub stars reported by the source. Last updated 2/24/2026.

View Source

Setup snapshot

git clone https://github.com/jarmentor/obsidian-notebook-mcp.git
  1. 1

    Setup complexity is MEDIUM. Standard integration tests and API key provisioning are required before connecting this to production workloads.

  2. 2

    Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.

Evidence Ledger

Everything public we have scraped or crawled about this agent, grouped by evidence type with provenance.

Verifiededitorial-content
Vendor (1)

Vendor

Jarmentor

profilemedium
Observed Feb 24, 2026Source linkProvenance
Compatibility (2)

Protocol compatibility

MCP

contracthigh
Observed Feb 24, 2026Source linkProvenance

Auth modes

mcp, api_key

contracthigh
Observed Feb 24, 2026Source linkProvenance
Artifact (1)

Machine-readable schemas

OpenAPI or schema references published

contracthigh
Observed Feb 24, 2026Source linkProvenance
Adoption (1)

Adoption signal

4 GitHub stars

profilemedium
Observed Feb 24, 2026Source linkProvenance
Security (1)

Handshake status

UNKNOWN

trustmedium
Observed unknownSource linkProvenance
Integration (1)

Crawlable docs

6 indexed pages on the official domain

search_documentmedium
Observed Apr 15, 2026Source linkProvenance

Release & Crawl Timeline

Merged public release, docs, artifact, benchmark, pricing, and trust refresh events.

Self-declaredagent-index

Docs Update

Docs refreshed: Sign in to GitHub · GitHub

search_documentmedium

Fresh crawlable documentation was indexed for the official domain.

Observed Apr 15, 2026

Artifacts Archive

Extracted files, examples, snippets, parameters, dependencies, permissions, and artifact metadata.

Self-declaredGITHUB MCP

Extracted files

0

Examples

6

Snippets

0

Languages

typescript

Executable Examples

bash

git clone <repository-url>
cd ai-note-searcher-5000

yaml

volumes:
  - /path/to/your/obsidian/notebook:/app/notebook:ro

bash

ollama pull nomic-embed-text:latest

bash

docker-compose up

bash

# Start the full stack
docker-compose up

# Rebuild after code changes
docker-compose build ai-note-searcher

# Force reindex all notes
docker-compose restart ai-note-searcher

# Clear vector database completely
docker-compose down && rm -rf qdrant_data && docker-compose up

bash

# Install dependencies
npm install

# Build TypeScript
npm run build

# Development with auto-reload
npm run dev

# Start the application
npm start

Docs & README

Full documentation captured from public sources, including the complete README when available.

Self-declaredGITHUB MCP

Docs source

GITHUB MCP

Editorial quality

ready

AI-powered semantic search for Obsidian notes using Qdrant AI Note Searcher 5000 A dockerized semantic search system for Obsidian notes that provides intelligent search capabilities through vector embeddings and an MCP (Model Context Protocol) server for LLM integration. Overview AI Note Searcher 5000 watches your Obsidian notebook folder, creates vector embeddings using Ollama, stores them in Qdrant, and provides semantic search capabilities through an MCP server that LLMs

Full README

AI Note Searcher 5000

A dockerized semantic search system for Obsidian notes that provides intelligent search capabilities through vector embeddings and an MCP (Model Context Protocol) server for LLM integration.

Overview

AI Note Searcher 5000 watches your Obsidian notebook folder, creates vector embeddings using Ollama, stores them in Qdrant, and provides semantic search capabilities through an MCP server that LLMs can use to search your notes intelligently.

Features

  • Real-time File Watching: Automatically processes markdown files as they're added or modified
  • Semantic Search: Vector-based similarity search using embeddings
  • Hybrid Search: Combines semantic and full-text search for better results
  • MCP Server: Model Context Protocol server for LLM integration
  • Docker Deployment: Fully containerized with persistent storage
  • Obsidian Integration: Designed specifically for Obsidian note structures
  • Frontmatter Support: Parses YAML frontmatter for metadata extraction

Architecture

Core Components

  • AINotesearcher: Main orchestrator that initializes all components
  • FileWatcher: Monitors Obsidian folder using chokidar for file changes
  • VectorProcessor: Handles text chunking and embedding generation via Ollama
  • QdrantClient: Vector database operations wrapper
  • MCPServer: Exposes search tools to LLMs via Model Context Protocol

Technology Stack

  • Node.js/TypeScript: Core application runtime
  • Qdrant: Vector database for embeddings storage
  • Ollama: Local embedding generation (nomic-embed-text:latest)
  • Docker Compose: Container orchestration
  • MCP SDK: Model Context Protocol implementation

Quick Start

Prerequisites

  • Docker and Docker Compose
  • Ollama running locally with nomic-embed-text:latest model
  • An Obsidian vault/notebook folder

Installation

  1. Clone the repository:
git clone <repository-url>
cd ai-note-searcher-5000
  1. Update the notebook path in docker-compose.yml:
volumes:
  - /path/to/your/obsidian/notebook:/app/notebook:ro
  1. Pull the Ollama model:
ollama pull nomic-embed-text:latest
  1. Start the services:
docker-compose up

The system will automatically:

  • Start Qdrant vector database on localhost:6333
  • Begin watching your notebook folder for changes
  • Process existing markdown files and create embeddings
  • Start the MCP server for LLM integration

Usage

Docker Commands

# Start the full stack
docker-compose up

# Rebuild after code changes
docker-compose build ai-note-searcher

# Force reindex all notes
docker-compose restart ai-note-searcher

# Clear vector database completely
docker-compose down && rm -rf qdrant_data && docker-compose up

Local Development

# Install dependencies
npm install

# Build TypeScript
npm run build

# Development with auto-reload
npm run dev

# Start the application
npm start

MCP Server Integration

For Claude Desktop integration, update your claude_desktop_config.json:

{
  "mcpServers": {
    "ai-note-searcher": {
      "command": "node",
      "args": ["/path/to/ai-note-searcher-5000/mcp-server.js"],
      "env": {
        "QDRANT_URL": "http://127.0.0.1:6333",
        "OLLAMA_URL": "http://127.0.0.1:11434",
        "NOTEBOOK_PATH": "/path/to/your/notebook",
        "MCP_SERVER": "true"
      }
    }
  }
}

Configuration

Environment Variables

| Variable | Default | Description | |----------|---------|-------------| | QDRANT_URL | http://qdrant:6333 | Vector database connection | | OLLAMA_URL | http://host.docker.internal:11434 | Ollama API endpoint | | NOTEBOOK_PATH | /app/notebook | Path to Obsidian folder | | EMBED_MODEL | nomic-embed-text:latest | Ollama embedding model | | MCP_SERVER | false | Disable console logging for MCP mode |

Search Features

  • Semantic similarity: Vector-based search using embeddings
  • Full-text matching: Literal text search in titles and content
  • Query expansion: Automatic date format conversion and keyword extraction
  • Low similarity threshold: 0.3 for maximum search fuzziness
  • Metadata search: Searches through frontmatter tags and properties

File Processing

  • Supports YAML frontmatter parsing
  • Chunks documents at ~1000 characters with 100 character overlap
  • Extracts titles from frontmatter or first H1 heading
  • Parses hashtags from content and frontmatter
  • Generates MD5 hashes as unique Qdrant point identifiers

MCP Tools Available

When integrated with an LLM via MCP, the following tools are available:

  • search_notes: Semantic search through your note collection
  • get_note_content: Retrieve full content of specific notes
  • Additional file management and directory tools

Monitoring

  • Qdrant Dashboard: http://localhost:6333/dashboard
  • Docker Logs: docker-compose logs --tail 50 ai-note-searcher
  • File Processing: Logs show chunk counts and processing status

Troubleshooting

Common Issues

  • "fetch failed" errors: Use 127.0.0.1 instead of localhost for URLs
  • No search results: Check Docker logs to verify file processing
  • MCP JSON parsing errors: Ensure MCP_SERVER=true to disable console logging
  • Connection refused: Verify Ollama is running and accessible

Development

For local development without Docker:

  1. Start Qdrant locally or use the Docker service
  2. Ensure Ollama is running on localhost:11434
  3. Set environment variables appropriately
  4. Use npm run dev for auto-reload

License

MIT License

Contributing

  1. Fork the repository
  2. Create a feature branch
  3. Make your changes
  4. Add tests if applicable
  5. Submit a pull request

Support

For issues and questions, please use the GitHub issue tracker.

Contract & API

Machine endpoints, protocol fit, contract coverage, invocation examples, and guardrails for agent-to-agent use.

Verifiedcapability-contract

Endpoints

Dossier APISnapshot APIContract APITrust API

Contract coverage

Status

ready

Auth

mcp, api_key

Streaming

No

Data region

global

Protocol support

MCP: verified

Requires: mcp, lang:typescript

Forbidden: none

Guardrails

Operational confidence: medium

Contract is available with explicit auth and schema references.
Trust confidence is not low and verification freshness is acceptable.
Protocol support is explicitly confirmed in contract metadata.
Invocation examples
curl -s "https://xpersona.co/api/v1/agents/mcp-jarmentor-obsidian-notebook-mcp/snapshot"
curl -s "https://xpersona.co/api/v1/agents/mcp-jarmentor-obsidian-notebook-mcp/contract"
curl -s "https://xpersona.co/api/v1/agents/mcp-jarmentor-obsidian-notebook-mcp/trust"

Reliability & Benchmarks

Trust and runtime signals, benchmark suites, failure patterns, and practical risk constraints.

Missingruntime-metrics

Trust signals

Handshake

UNKNOWN

Confidence

unknown

Attempts 30d

unknown

Fallback rate

unknown

Runtime metrics

Observed P50

unknown

Observed P95

unknown

Rate limit

unknown

Estimated cost

unknown

No benchmark suites or observed failure patterns are available.

Media & Demo

Every public screenshot, visual asset, demo link, and owner-provided destination tied to this agent.

Missingno-media
No screenshots, media assets, or demo links are available.

Related Agents

Neighboring agents from the same protocol and source ecosystem for comparison and shortlist building.

Self-declaredprotocol-neighbors
GITLAB_AI_CATALOGgitlab-mcp

Rank

83

A Model Context Protocol (MCP) server for GitLab

Traction

No public download signal

Freshness

Updated 2d ago

MCP
GITLAB_PUBLIC_PROJECTSgitlab-mcp

Rank

80

A Model Context Protocol (MCP) server for GitLab

Traction

No public download signal

Freshness

Updated 2d ago

MCP
GITLAB_AI_CATALOGrmcp-openapi

Rank

74

Expose OpenAPI definition endpoints as MCP tools using the official Rust SDK for the Model Context Protocol (https://github.com/modelcontextprotocol/rust-sdk)

Traction

No public download signal

Freshness

Updated 2d ago

MCP
GITLAB_AI_CATALOGrmcp-actix-web

Rank

72

An actix_web backend for the official Rust SDK for the Model Context Protocol (https://github.com/modelcontextprotocol/rust-sdk)

Traction

No public download signal

Freshness

Updated 2d ago

MCP
Agent hubMore from this sourceMCP agents
Machine Appendix

Contract JSON

{
  "contractStatus": "ready",
  "authModes": [
    "mcp",
    "api_key"
  ],
  "requires": [
    "mcp",
    "lang:typescript"
  ],
  "forbidden": [],
  "supportsMcp": true,
  "supportsA2a": false,
  "supportsStreaming": false,
  "inputSchemaRef": "https://github.com/jarmentor/obsidian-notebook-mcp#input",
  "outputSchemaRef": "https://github.com/jarmentor/obsidian-notebook-mcp#output",
  "dataRegion": "global",
  "contractUpdatedAt": "2026-02-24T19:46:55.598Z",
  "sourceUpdatedAt": "2026-02-24T19:46:55.598Z",
  "freshnessSeconds": 4440777
}

Invocation Guide

{
  "preferredApi": {
    "snapshotUrl": "https://xpersona.co/api/v1/agents/mcp-jarmentor-obsidian-notebook-mcp/snapshot",
    "contractUrl": "https://xpersona.co/api/v1/agents/mcp-jarmentor-obsidian-notebook-mcp/contract",
    "trustUrl": "https://xpersona.co/api/v1/agents/mcp-jarmentor-obsidian-notebook-mcp/trust"
  },
  "curlExamples": [
    "curl -s \"https://xpersona.co/api/v1/agents/mcp-jarmentor-obsidian-notebook-mcp/snapshot\"",
    "curl -s \"https://xpersona.co/api/v1/agents/mcp-jarmentor-obsidian-notebook-mcp/contract\"",
    "curl -s \"https://xpersona.co/api/v1/agents/mcp-jarmentor-obsidian-notebook-mcp/trust\""
  ],
  "jsonRequestTemplate": {
    "query": "summarize this repo",
    "constraints": {
      "maxLatencyMs": 2000,
      "protocolPreference": [
        "MCP"
      ]
    }
  },
  "jsonResponseTemplate": {
    "ok": true,
    "result": {
      "summary": "...",
      "confidence": 0.9
    },
    "meta": {
      "source": "GITHUB_MCP",
      "generatedAt": "2026-04-17T05:19:53.092Z"
    }
  },
  "retryPolicy": {
    "maxAttempts": 3,
    "backoffMs": [
      500,
      1500,
      3500
    ],
    "retryableConditions": [
      "HTTP_429",
      "HTTP_503",
      "NETWORK_TIMEOUT"
    ]
  }
}

Trust JSON

{
  "status": "unavailable",
  "handshakeStatus": "UNKNOWN",
  "verificationFreshnessHours": null,
  "reputationScore": null,
  "p95LatencyMs": null,
  "successRate30d": null,
  "fallbackRate": null,
  "attempts30d": null,
  "trustUpdatedAt": null,
  "trustConfidence": "unknown",
  "sourceUpdatedAt": null,
  "freshnessSeconds": null
}

Capability Matrix

{
  "rows": [
    {
      "key": "MCP",
      "type": "protocol",
      "support": "supported",
      "confidenceSource": "contract",
      "notes": "Confirmed by capability contract"
    },
    {
      "key": "obsidian",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "semantic-search",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "qdrant",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "mcp",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "vector-database",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    }
  ],
  "flattenedTokens": "protocol:MCP|supported|contract capability:obsidian|supported|profile capability:semantic-search|supported|profile capability:qdrant|supported|profile capability:mcp|supported|profile capability:vector-database|supported|profile"
}

Facts JSON

[
  {
    "factKey": "docs_crawl",
    "category": "integration",
    "label": "Crawlable docs",
    "value": "6 indexed pages on the official domain",
    "href": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceUrl": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceType": "search_document",
    "confidence": "medium",
    "observedAt": "2026-04-15T05:03:46.393Z",
    "isPublic": true
  },
  {
    "factKey": "protocols",
    "category": "compatibility",
    "label": "Protocol compatibility",
    "value": "MCP",
    "href": "https://xpersona.co/api/v1/agents/mcp-jarmentor-obsidian-notebook-mcp/contract",
    "sourceUrl": "https://xpersona.co/api/v1/agents/mcp-jarmentor-obsidian-notebook-mcp/contract",
    "sourceType": "contract",
    "confidence": "high",
    "observedAt": "2026-02-24T19:46:55.598Z",
    "isPublic": true
  },
  {
    "factKey": "auth_modes",
    "category": "compatibility",
    "label": "Auth modes",
    "value": "mcp, api_key",
    "href": "https://xpersona.co/api/v1/agents/mcp-jarmentor-obsidian-notebook-mcp/contract",
    "sourceUrl": "https://xpersona.co/api/v1/agents/mcp-jarmentor-obsidian-notebook-mcp/contract",
    "sourceType": "contract",
    "confidence": "high",
    "observedAt": "2026-02-24T19:46:55.598Z",
    "isPublic": true
  },
  {
    "factKey": "schema_refs",
    "category": "artifact",
    "label": "Machine-readable schemas",
    "value": "OpenAPI or schema references published",
    "href": "https://github.com/jarmentor/obsidian-notebook-mcp#input",
    "sourceUrl": "https://xpersona.co/api/v1/agents/mcp-jarmentor-obsidian-notebook-mcp/contract",
    "sourceType": "contract",
    "confidence": "high",
    "observedAt": "2026-02-24T19:46:55.598Z",
    "isPublic": true
  },
  {
    "factKey": "vendor",
    "category": "vendor",
    "label": "Vendor",
    "value": "Jarmentor",
    "href": "https://github.com/jarmentor/obsidian-notebook-mcp",
    "sourceUrl": "https://github.com/jarmentor/obsidian-notebook-mcp",
    "sourceType": "profile",
    "confidence": "medium",
    "observedAt": "2026-02-24T19:43:14.176Z",
    "isPublic": true
  },
  {
    "factKey": "traction",
    "category": "adoption",
    "label": "Adoption signal",
    "value": "4 GitHub stars",
    "href": "https://github.com/jarmentor/obsidian-notebook-mcp",
    "sourceUrl": "https://github.com/jarmentor/obsidian-notebook-mcp",
    "sourceType": "profile",
    "confidence": "medium",
    "observedAt": "2026-02-24T19:43:14.176Z",
    "isPublic": true
  },
  {
    "factKey": "handshake_status",
    "category": "security",
    "label": "Handshake status",
    "value": "UNKNOWN",
    "href": "https://xpersona.co/api/v1/agents/mcp-jarmentor-obsidian-notebook-mcp/trust",
    "sourceUrl": "https://xpersona.co/api/v1/agents/mcp-jarmentor-obsidian-notebook-mcp/trust",
    "sourceType": "trust",
    "confidence": "medium",
    "observedAt": null,
    "isPublic": true
  }
]

Change Events JSON

[
  {
    "eventType": "docs_update",
    "title": "Docs refreshed: Sign in to GitHub · GitHub",
    "description": "Fresh crawlable documentation was indexed for the official domain.",
    "href": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceUrl": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceType": "search_document",
    "confidence": "medium",
    "observedAt": "2026-04-15T05:03:46.393Z",
    "isPublic": true
  }
]

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