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https://github.com/deepset-ai/spring-into-haystack

🌱 Sprout an Agent with Haystack & MCP

https://github.com/deepset-ai/spring-into-haystack

Science Score: 26.0%

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    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
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    .zenodo.json file
    Found .zenodo.json file
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    Scientific vocabulary similarity
    Low similarity (12.5%) to scientific vocabulary
Last synced: 5 months ago · JSON representation

Repository

🌱 Sprout an Agent with Haystack & MCP

Basic Info
Statistics
  • Stars: 2
  • Watchers: 1
  • Forks: 18
  • Open Issues: 0
  • Releases: 0
Created 11 months ago · Last pushed 10 months ago
Metadata Files
Readme License

README.md

Spring into haystack logo with flowers, bee and butterfly on the logo, giving spring vibes

Welcome to the 🌸 Spring Into Haystack 🌸 your chance to cultivate something useful, elegant, and powerful — just like spring itself! 🌼

🪻 Your Spring Challenge

Your mission is to build a tool-using Haystack Agent that acts as an MCP Client and connects to the GitHub MCP Server. Once connected, your Agent will be able to call GitHub tools — all through the power of the Model Context Protocol.

To get started, check out the scaffolded starter code in github-agent.py. You’ll need to: - Implement the missing parts - Configure your Agent to connect to the GitHub MCP server - Make sure the Agent can reason and act based on tool outputs

Note: The official GitHub MCP Server requires Docker to run. If you're unable to use Docker (e.g. due to system limitations or permissions), you can use the legacy GitHub MCP Server, which is deprecated but can be run easily run with npx. Note that the set of available tools differs between the official and legacy servers.

✅ Test Your Agent: Find the Hidden Typo

To verify your Agent is working correctly, we’ve planted a typo somewhere in this very README.

Once your Agent is fully wired up and reasoning correctly, it should: 1. Detect the typo by reading this README via the GitHub MCP server
2. Open a GitHub issue describing the typo clearly in the issue body

This will prove that your Agent can: - Understand the task and make a plan - Select the right tool(s) from the GitHub MCP server - Execute an action on GitHub

🌷 Start Building

  1. Fork this repo on GitHub
  2. Fill in the missing peices in github-agent.py to build your MCP-connected Agent
  3. Once you're done, check out solution.py to compare your implementation.

Requirements:

Install Dependencies

pip install -r requirements.txt

Note: The mcp-haystack package requires Python ≥ 3.10

Components:

  • Agent – component for the smart decision-maker
  • MCPTool – lets your agent talk to the MCP Server

Owner

  • Name: deepset
  • Login: deepset-ai
  • Kind: organization
  • Email: hello@deepset.ai
  • Location: Berlin, Germany

Building enterprise search systems powered by latest NLP & open-source.

GitHub Events

Total
  • Issues event: 4
  • Watch event: 2
  • Issue comment event: 6
  • Push event: 4
  • Public event: 1
  • Pull request event: 8
  • Fork event: 18
Last Year
  • Issues event: 4
  • Watch event: 2
  • Issue comment event: 6
  • Push event: 4
  • Public event: 1
  • Pull request event: 8
  • Fork event: 18

Issues and Pull Requests

Last synced: 6 months ago

Dependencies

requirements.txt pypi
  • haystack-ai ==2.12.2
  • mcp-haystack *