codefactor-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| CODEFACTOR_COOKIE | No | Optional browser Cookie header for authenticated access to CodeFactor. | |
| CODEFACTOR_REPOSITORY_URL | No | Default CodeFactor repository URL to use if no url argument is provided. |
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
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
| prompts | {
"listChanged": true
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| parse_codefactor_htmlB | Parse a CodeFactor repository issues HTML response and return normalized issues. |
| fetch_codefactor_issuesB | Fetch CodeFactor repository issues from codefactor.io and return normalized issue data. |
| build_codefactor_promptC | Build an AI-facing prompt that asks the model to follow CodeFactor suggestions while editing code. |
| summarize_codefactor_issuesC | Return a compact Markdown summary of CodeFactor issues for quick context. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
| follow-codefactor-advice | Prompt an AI coding agent to use CodeFactor issues as quality guidance before editing. |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 4 tools
Each tool serves a distinct purpose: building a prompt, fetching issues, parsing HTML, and summarizing. No overlap in functionality.
All tool names follow a consistent verb_noun pattern (build_, fetch_, parse_, summarize_) with clear domain context.
4 tools is an appropriate size for a focused server providing CodeFactor issue access and summarization without being too sparse or overwhelming.
Covers key operations: fetching, parsing, summarizing issues, and generating a prompt. Minor gap: no tool to act on issues directly, but prompt builder handles that indirectly.