Skip to main content

HyperX MCP Server

Connect Claude to your HyperX knowledge graph using the Model Context Protocol (MCP).

Installation

pip install hyperx-mcp

Or install from source:

cd hyperx-mcp
pip install -e .

Configuration

Environment Variables

Variable Required Default Description
HYPERX_API_KEY Yes - Your HyperX API key
HYPERX_BASE_URL No https://api.hyperxdb.dev API base URL
HYPERX_ACCESS_LEVEL No explore Tool access level: read, explore, or full

Claude Desktop Configuration

Add to your Claude Desktop config file:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json Windows: %APPDATA%\Claude\claude_desktop_config.json

{
  "mcpServers": {
    "hyperx": {
      "command": "hyperx-mcp",
      "env": {
        "HYPERX_API_KEY": "your-api-key-here",
        "HYPERX_ACCESS_LEVEL": "explore"
      }
    }
  }
}

Alternative: Using uvx (no install required)

{
  "mcpServers": {
    "hyperx": {
      "command": "uvx",
      "args": ["hyperx-mcp"],
      "env": {
        "HYPERX_API_KEY": "your-api-key-here"
      }
    }
  }
}

Available Tools

Read Level (read)

Basic read-only access for RAG applications.

Tool Description
hyperx_search Hybrid search (vector + text) for entities
hyperx_lookup Get entity by ID
hyperx_paths Find paths between entities

Explore Level (explore)

Extended read access for graph exploration.

Tool Description
hyperx_explorer Explore entity neighborhood
hyperx_explain Natural language entity explanation
hyperx_relationships Get entity relationships

Full Level (full)

Complete access including mutations.

Tool Description
hyperx_entity_crud Create, update, delete entities
hyperx_hyperedge_crud Create, update, delete hyperedges

Quality Signals

All tool responses include quality signals to help Claude self-correct:

{
  "success": true,
  "data": { ... },
  "quality": {
    "confidence": 0.85,
    "coverage": 0.72,
    "diversity": 0.68,
    "should_retrieve_more": false,
    "suggested_refinements": ["Try searching for 'transformer attention'"]
  }
}
  • confidence: Overall result quality (0.0-1.0)
  • coverage: How well results cover the query
  • diversity: Entity type diversity in results
  • should_retrieve_more: Hint to expand search
  • suggested_refinements: Query improvement suggestions

Example Usage

Once configured, you can ask Claude:

"Search my knowledge graph for information about transformer architectures"

"Find the connection between BERT and GPT in the knowledge graph"

"Explore all entities related to machine learning within 2 hops"

"Create a new concept entity for 'Retrieval Augmented Generation'"

Development

# Install dev dependencies
pip install -e ".[dev]"

# Run tests
pytest

# Run linter
ruff check .

Troubleshooting

"HYPERX_API_KEY environment variable is required"

Make sure you've set the API key in your Claude Desktop config or environment.

Tools not appearing in Claude

  1. Restart Claude Desktop after config changes
  2. Check the config file path is correct for your OS
  3. Verify the hyperx-mcp command is in your PATH

Connection errors

  1. Check your API key is valid
  2. Verify network connectivity to api.hyperxdb.dev
  3. Check if you need to set a custom HYPERX_BASE_URL

License

MIT

Metadata

Release files for hyperx-mcp 0.1.2

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for hyperx-mcp 0.1.2
File Size Uploaded
hyperx_mcp-0.1.2.tar.gz 5.3 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for hyperx-mcp 0.1.2
File Interpreter ABI Platform
hyperx_mcp-0.1.2-py3-none-any.whl Python 3 none any Details

Total release size: 11.2 kB

Release files / hyperx_mcp-0.1.2.tar.gz

Download URL hyperx_mcp-0.1.2.tar.gz
Size 5.3 kB
Tags Source
SHA-256 checksum
How to use checksums
2d399c30275428ebd9c2f6461e81bae1f9a48dec1e699f8e9f05ed89b599f6cd
BLAKE2b-256 checksum
How to use checksums
65f2412e76609b7b3efaa5423e6d558091c4035a600e2516dab6e86b42275ac3
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/6.1.0 CPython/3.13.7

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Jan 18, 2026.

Transparency log

Release files / hyperx_mcp-0.1.2-py3-none-any.whl

Download URL hyperx_mcp-0.1.2-py3-none-any.whl
Size 5.9 kB
Tags Python 3
SHA-256 checksum
How to use checksums
2a4251df4d660c648eb7a6401b9d1192ee8c7fa6db07a46c501e2e2171f8bcbe
BLAKE2b-256 checksum
How to use checksums
e77830e90a0647c181761b162ccd0b11d92617e1855ec586f0a378a9a54bd9c4
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/6.1.0 CPython/3.13.7

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Jan 18, 2026.

Transparency log

Release history Release notifications | RSS feed

This release

0.1.2 This release

2 release files

0.1.1

2 release files

0.1.0

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page