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Perfrunner MCP Server

Perfrunner MCP Server

Local
github.com/sudosalimDeveloper Tools0Updated 78w ago

About Perfrunner MCP Server

Perfrunner MCP Server is a prototype for querying static perfrunner test and cluster configurations. It is aimed at performance teams working with infrastructure configuration data stored in Couchbase.

Key features

  1. 01Access test configurations
  2. 02Access cluster configurations
  3. 03Store configurations and results in Couchbase
  4. 04Use full-text search

Use cases

  1. 01Look up a perfrunner test configuration
  2. 02Inspect cluster configuration data
  3. 03Search stored performance configuration records

MCP support

Provides MCP access to perfrunner configuration information, including test and cluster configurations.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

No install method listed yet

We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.

Repository

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

Perfrunner MCP Server

A Model Context Protocol (MCP) that provide info on the perfrunner static configurations. i.e test and cluster configurations.

Overview

Prototype and toy playground for an MCP server to talk with perf team's infrastructure.

Features

  • Integrates with Couchbase server for storing test configurations and results
  • Backed by Full Text Search (FTS)
  • Basic MCP

Configuration

Create a .env file in the project root with necessary configuration (you can copy and modify the provided .env.example file):

cp .env.example .env
# Edit the .env file with your specific configuration

Running the MCP Server

make

Loading Data

scripts/configs_to_server.py is used to load .test and .spec files into your Couchbase server cluster.

To load test files, use:

uv run scripts/configs_to_server.py test path/to/my/test-directory/

And to load cluster spec use:

uv run scripts/configs_to_server.py cluster path/to/my/cluster-spec-directory/

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