Developer tools · MCP server
Eval view: MCP server, setup and security
Eval view is an open-source MCP server that lets an AI agent compare agent behavior against saved baselines and block regressions in CI. Its repository has 140 stars and its last commit is from October 16, 2026 and it is licensed under Apache-2.0.
| Adoption (stars) | 21/40 | |
|---|---|---|
| Maintenance | 30/30 | |
| Framework (licence, registry, official) | 20/30 |
What Eval view does
According to its repository: “Regression testing for AI agents: save golden baselines, detect behavioral drift and block regressions in CI.”
An MCP server gives an AI agent extra tools it calls during the conversation: the agent reads their description, decides to use them and gets the result back. Eval view is listed under Developer tools, a category of 475 servers in the directory, where it ranks #153 by stars.
Topics declared by the repository: agent-benchmark, agent-evaluation, ai-agents, crewai, evaluation, langgraph.
Installing and connecting Eval view
Distribution modes declared in the official MCP registry:
- PyPI package (Python, started with
uvxorpip)
Like any MCP server, you declare it in your client's configuration (Claude Desktop, Claude Code, Cursor, VS Code, Codex…): a name, the command that starts it or its URL, and any environment variables. The client then starts it and lists its tools. Project language: Python. Listed systems: macOS, Windows, Linux.
The registry lists one secret variable to provide (API key, access token). Keep them in the client's environment variables, never in a shared file or a repository.
Security: what to check
An MCP server runs code with the rights you give it, and the model reads its tool descriptions: a malicious or compromised server can hijack the agent. Read the code, or pick a maintained and widely used server, before connecting it.
Points found for Eval view:
- Secrets: the server acts with your credentials. Create a dedicated key with minimum rights and an expiry date.
Good practice: grant only the rights needed (least privilege), require human approval for irreversible actions, and run the AI agent security check.
Project activity and maintenance
Created on November 17, 2025, the hidai25/eval-view repository has 140 stars and 27 forks, with 2 open issues. It has more stars than 72% of the servers in the directory. It received changes this month. Version published in the registry: 0.6.0 (March 27, 2026).
Stars measure attention, not quality: a recent, heavily promoted project can collect them fast, while a useful but niche server will have few.
Verdict
Eval view is a reasonable choice; check the points below before connecting it.
Strengths
- Active project: recent commit
- Listed in the official MCP registry
- Permissive licence (Apache-2.0)
Limitations
- Requires an API key or token
Avoid if…
- You do not want to give credentials to an agent
Alternatives
- Radar Kubernetes MCP Server3.9K ★
- Repowise7.9K ★
- Jscpd6.4K ★
- Apify MCP server12.9K ★
- Codebase Memory47.4K ★
- PostHog MCP Server40.4K ★
Learn more
Frequently asked questions
How do I install Eval view?
Eval view is distributed as PyPI package (Python, started with uvx or pip). Add it to your client's MCP configuration (Claude Desktop, Cursor, VS Code…) following the README of hidai25/eval-view.
Is Eval view free?
The code is published under the Apache-2.0 licence and can be used free of charge. It needs an API key: the service it connects to may be paid.
Is Eval view safe?
Points to watch: secrets. Give it minimum rights and approve sensitive actions.
Is it an official server?
Nothing says so: it is a project published by hidai25 on GitHub. Check who maintains it before giving it access.
What are the alternatives to Eval view?
In the same category: Radar Kubernetes MCP Server, Repowise, Jscpd, and Apify MCP server. Radar Kubernetes MCP Server and Repowise score higher on our grid.
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Neutrality. No affiliate links. No vendor pays to be reviewed, rated or ranked. Reviews are directed by François Chollet, neutral and factual, and every data point is dated and sourced. How we score