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evalscopebench-mcp

evalscopebench-mcp

Remote
github.com/clauxelDeveloper Tools0Updated 22w ago
Repository

About evalscopebench-mcp

evalscopebench-mcp is a paid hosted MCP for an AI SDK benchmark dashboard, aimed at AI agents and coding teams. Its tools run benchmark checks, compare model scores, and produce reports and receipts.

Key features

  1. 01Run benchmark gates
  2. 02Compare model scores
  3. 03Read benchmark reports
  4. 04Issue benchmark receipts
  5. 05Token-based access and usage receipts

Use cases

  1. 01Run benchmark checks in an AI workflow
  2. 02Compare scores across models
  3. 03Review reports and retain benchmark receipts

MCP support

The hosted remote MCP exposes structured JSON tools over its endpoint, with bearer-token access required for production calls.

Configuration

Remote servers need no local install. Pick your client, then copy the config or install in one click.

Endpointhttps://evalscopebench.clauxel.com/mcp
Copy install command
Claude CodeTerminal
Cursor.cursor/mcp.json
VS Code.vscode/mcp.json
Claude Desktopclaude_desktop_config.json
Windsurf~/.codeium/windsurf/mcp_config.json

Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.

All endpoints
Streamable HTTPhttps://evalscopebench.clauxel.com/mcpAuth required

Tools

Details

From the project README

EvalScope Benchmark MCP

Hosted MCP for AI SDK benchmark dashboard.

EvalScope Benchmark MCP is a paid remote MCP endpoint for AI SDK benchmark dashboard. It exposes structured JSON tools, a public server card, token-based access, usage receipts, and audit-ready workflow evidence for AI agents and coding teams.

Public Endpoints

Access

This is a paid hosted remote MCP. Production calls require a bearer token issued from the product website.

Authorization: Bearer <token>

Unauthenticated browser visits to /mcp return a clear JSON error instead of internal details.

Tools

  • run_benchmark_gate
  • compare_model_scores
  • read_benchmark_report
  • issue_benchmark_receipt

Quick Start

  1. Open the website and choose a plan.
  2. Create or request an API token.
  3. Add the endpoint to an MCP client that supports Streamable HTTP remote servers.
  4. Send JSON-RPC requests with the bearer token.

Useful Links

Status

This repository is a public documentation and directory-submission reference for the hosted service. It does not contain the private production source code.

Comments

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.