# DataBridge

> Use this tool when you need to integrate AI applications with a local database for persistent storage and retrieval of contextual information. DataBridge solves problems like maintaining conversation history and building knowledge bases from user interactions by providing tools for ingesting user observations and retrieving relevant information based on user queries. It takes in user observations and queries as inputs and outputs relevant information, making it suitable for use cases requiring efficient and simple data management in development and production environments.

Canonical page: https://skillsregistry.net/skills/databridge-org-databridge  
JSON: https://api.skillsregistry.net/v1/skills/databridge-org-databridge

## Description

This MCP server implementation provides a bridge to DataBridge, enabling AI assistants to ingest and retrieve information from a local database. Developed as part of the databridge-mcp project, it offers two main tools: one for ingesting user observations with metadata, and another for retrieving relevant information based on user queries. The server uses FastMCP for efficient request handling and is designed to work with Python 3.11+. It's particularly useful for AI applications requiring persistent storage and retrieval of contextual information, supporting use cases like maintaining conversation history or building knowledge bases from user interactions. The implementation focuses on simplicity and ease of integration, making it suitable for both development and production environments.

## Trust

- **Trust score (0–1):** 0.89
- **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/databridge-org-databridge)
- **Repository:** <https://github.com/morphik-org/morphik-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": "databridge-org-databridge"
    }
  }
}
```

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