PocketFlow MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| MODEL | No | Specific model to use | |
| API_KEY | Yes | API key for the LLM provider | |
| LANGUAGE | No | Tutorial language | english |
| REPO_URL | No | GitHub repository URL | |
| USE_CACHE | No | Enable LLM response caching | true |
| LLM_PROVIDER | No | AI provider (openrouter, google, anthropic, openai) | |
| MAX_FILE_SIZE | No | Maximum file size in bytes | 100000 |
| EXCLUDE_PATTERNS | No | File patterns to skip (comma-separated) | |
| INCLUDE_PATTERNS | No | File patterns to analyze (comma-separated) | |
| MAX_ABSTRACTIONS | No | Number of key concepts to identify | 10 |
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 |
|---|---|
| analyze_github_repositoryB | Analyze a GitHub repository and generate a comprehensive tutorial following the PocketFlow methodology |
| get_repository_structureC | Get the file structure of a GitHub repository |
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 2 tools
The two tools have clearly distinct purposes: analyze_github_repository generates a tutorial, while get_repository_structure retrieves file structure. There is no overlap or ambiguity between these functions, making it easy for an agent to select the correct tool.
Both tools follow a consistent verb_noun pattern (analyze_github_repository, get_repository_structure) with clear, descriptive names. The naming is uniform and predictable, enhancing usability.
With only 2 tools, the server feels thin for its apparent domain of GitHub repository analysis and tutorial generation. A more complete set might include tools for updating tutorials, managing analysis results, or handling other repository aspects, suggesting an under-scoped implementation.
The tool surface is severely incomplete for the PocketFlow methodology domain. It lacks essential operations such as creating, updating, or deleting tutorials, managing user interactions, or handling errors, which are likely needed for a comprehensive workflow, leading to potential agent failures.