# Recall

> Use this tool when you need to quickly search and retrieve specific information from markdown files and meeting transcripts. Recall solves the problem of manually combing through large amounts of text data by indexing and enabling semantic search, allowing for efficient retrieval of relevant information. It takes in markdown files and meeting transcripts as input and outputs relevant search results, making it ideal for use cases where local, private, and fast search functionality is required.

Canonical page: https://skillsregistry.net/skills/thetenzinwoser-recall  
JSON: https://api.skillsregistry.net/v1/skills/thetenzinwoser-recall

## Description

Indexes markdown files and Granola meeting transcripts into a local vector database for semantic search. Uses Ollama with nomic-embed-text for embeddings and ChromaDB for vector storage, running entirely on the local machine with no API keys or cloud dependencies. Includes auto-indexing via macOS LaunchAgent and tools for searching, fetching transcripts, and managing indexes.

## Trust

- **Trust score (0–1):** 0.77
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** database
- **Updated:** 2026-09-28

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/thetenzinwoser-recall)
- **Repository:** <https://github.com/thetenzinwoser/recall-mcp>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "thetenzinwoser-recall"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/thetenzinwoser-recall` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/thetenzinwoser-recall/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt