revibe-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| REVIBE_API_KEY | No | Your Revibe API key for manual authentication. Get it from https://app.revibe.codes/settings |
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
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| revibe_loginA | Log in to Revibe via browser. Opens a browser window for authentication. After logging in and clicking Authorize, the API key is saved locally so all other Revibe tools work automatically. |
| analyze_repoA | Submit a GitHub repository for Revibe analysis. Analyzes architecture, file roles, execution flows, system design Q&A, and more. If no URL is provided, auto-detects from the current git remote. Analysis takes 3-7 minutes for most repos. |
| check_statusB | Check the status of a Revibe analysis job. |
| get_summaryB | Get a condensed summary of a completed Revibe analysis. Shows architecture pattern, language, file count, key modules, and available sections. |
| get_sectionA | Get a specific analysis section from a completed Revibe analysis. Available sections:
|
| get_agent_contextA | Get the full agent context JSON for a completed analysis. This is a structured format optimized for AI agents, containing file index, dependency graph, architecture layers, call chains, constraints, design decisions, and database schema. Save the output to agent_context.json for persistent codebase understanding. |
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 6 tools
Each tool has a distinct role: login for authentication, analyze_repo for submission, check_status for job monitoring, and three retrieval tools with clear separation of scope. get_summary, get_section, and get_agent_context serve different granularities of output, preventing confusion.
Most tools follow a clear verb_noun pattern (analyze_repo, check_status, get_summary, get_section, get_agent_context). The exception is revibe_login, which places a brand prefix before a verb and does not match the conventional verb-first structure, creating a minor inconsistency.
With 6 tools, the server is well-scoped for its purpose: authentication, analysis submission, status polling, and result retrieval. This is an appropriate size that covers the workflow without redundancy or unnecessary bloat.
The tool set covers the complete lifecycle of a Revibe analysis: login, submit repository, check progress, and retrieve results in multiple formats (summary, sections, and full agent context). No critical steps are missing for the intended use case, and the output options are sufficient for both human and agent consumption.