Code Review MCP
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Server capabilities have not been inspected yet.
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| code-reviewC | Run an AI-powered code review for a GitHub PR. Usage: @code-review [prId] [--flags] |
| github.resolve_prD | Resolve owner/repo and PR number from an input |
| github.fetch_filesC | Fetch files/diff for a PR |
| jira.fetchC | Fetch Jira tickets by keys or from prMeta |
| analysis.run_staticC | Run ESLint/tsc/Prettier on files |
| security.run_semgrepD | Run Semgrep scan |
| tests.run_playwrightD | Run Playwright tests |
| report.generateC | Generate a code review report markdown |
| cleanup.pruneC | Prune old logs and reports |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 9 tools
Most tools have distinct purposes, such as static analysis, security scanning, and test running, but there is some potential overlap between 'analysis.run_static' and 'security.run_semgrep' as both involve code analysis, which could cause confusion. The descriptions help clarify their focuses, but the boundaries are not perfectly clear.
The naming conventions are inconsistent, mixing dot notation (e.g., 'analysis.run_static'), hyphenated names (e.g., 'code-review'), and snake_case (e.g., 'github.fetch_files'). There is no uniform pattern, making the set less predictable and harder for agents to parse reliably.
With 9 tools, the count is well-scoped for a code review server, covering key areas like analysis, security, testing, reporting, and integration with GitHub and Jira. Each tool appears to serve a specific function without redundancy, fitting the domain appropriately.
The toolset covers core code review workflows, including fetching PR data, running analyses, generating reports, and integrating with external systems. A minor gap is the lack of tools for managing or updating review comments or statuses, but agents can work around this with the existing tools.