MCP Reference - Skill Seekers

May 30, 2026 · View on GitHub

Version: 3.6.0
Last Updated: 2026-04-09
Complete reference for 40 MCP tools

Overview
Tool Categories
Tool Reference
Common Patterns
Error Handling

Overview

What is MCP?

MCP (Model Context Protocol) allows AI agents like Claude Code to interact with Skill Seekers through a standardized interface. Instead of running CLI commands, you can use natural language:

"Scrape the React documentation and create a skill"
"Package the output/react skill for Claude"
"List available workflow presets"

Transport Modes

The MCP server supports two transport modes:

Mode	Use Case	Command
stdio	Claude Code, VS Code + Cline	`skill-seekers-mcp`
HTTP	Cursor, Windsurf, HTTP clients	`skill-seekers-mcp --transport http --port 8765`

Starting the Server

# stdio mode (default)
skill-seekers-mcp

# HTTP mode
skill-seekers-mcp --transport http --port 8765

# With custom host
skill-seekers-mcp --transport http --host 0.0.0.0 --port 8765

Tool Categories

Core Tools (9)

Essential tools for basic skill creation workflow:

Tool	Purpose
`list_configs`	List preset configurations
`generate_config`	Generate config from docs URL
`validate_config`	Validate config structure
`estimate_pages`	Estimate page count
`scrape_docs`	Scrape documentation
`package_skill`	Package to .zip
`upload_skill`	Upload to platform
`enhance_skill`	AI enhancement
`install_skill`	Complete workflow

Extended Tools (10)

Advanced scraping and analysis tools:

Tool	Purpose
`scrape_github`	GitHub repository analysis
`scrape_pdf`	PDF extraction
`scrape_video`	Video transcript extraction
`scrape_codebase`	Local codebase analysis
`scrape_generic`	Generic scraper for 10 new source types
`sync_config`	Sync config from remote source
`detect_patterns`	Pattern detection
`extract_test_examples`	Extract usage examples from tests
`build_how_to_guides`	Generate how-to guides
`extract_config_patterns`	Extract configuration patterns

Config Source Tools (5)

Manage configuration sources:

Tool	Purpose
`add_config_source`	Register git repo as config source
`list_config_sources`	List registered sources
`remove_config_source`	Remove config source
`fetch_config`	Fetch configs from git
`submit_config`	Submit config to source

Config Splitting Tools (2)

Handle large documentation:

Tool	Purpose
`split_config`	Split large config
`generate_router`	Generate router skill

Config Publishing Tools (1)

Push configs to registered source repositories:

Tool	Purpose
`push_config`	Push validated config to a registered config source repo

Marketplace Tools (4)

Manage plugin marketplace repositories:

Tool	Purpose
`add_marketplace`	Register a marketplace repository
`list_marketplaces`	List registered marketplaces
`remove_marketplace`	Remove a marketplace
`publish_to_marketplace`	Publish skill to a marketplace repo

Vector Database Tools (4)

Export to vector databases:

Tool	Purpose
`export_to_weaviate`	Export to Weaviate
`export_to_chroma`	Export to ChromaDB
`export_to_faiss`	Export to FAISS
`export_to_qdrant`	Export to Qdrant

Workflow Tools (5)

Manage enhancement workflows:

Tool	Purpose
`list_workflows`	List all workflows
`get_workflow`	Get workflow YAML
`create_workflow`	Create new workflow
`update_workflow`	Update workflow
`delete_workflow`	Delete workflow

Tool Reference

Core Tools

list_configs

List all available preset configurations.

Parameters: None

Returns: Array of config objects

{
  "configs": [
    {
      "name": "react",
      "description": "React documentation",
      "source": "bundled"
    }
  ]
}

Example:

# Natural language
"List available configurations"
"What configs are available?"
"Show me the preset configs"

generate_config

Generate a configuration file from a documentation URL.

Parameters:

Name	Type	Required	Description
`url`	string	Yes	Documentation URL
`name`	string	No	Config name (auto-detected)
`description`	string	No	Description (auto-detected)

Returns: Config JSON object

Example:

# Natural language
"Generate a config for https://docs.django.com/"
"Create a Django config"
"Make a config from the React docs URL"

validate_config

Validate a configuration file structure.

Parameters:

Name	Type	Required	Description
`config`	object/string	Yes	Config object or file path

Returns: Validation result

{
  "valid": true,
  "errors": [],
  "warnings": []
}

Example:

# Natural language
"Validate this config: {config_json}"
"Check if my config is valid"
"Validate configs/react.json"

estimate_pages

Estimate total pages for documentation scraping.

Parameters:

Name	Type	Required	Description
`config`	object/string	Yes	Config object or file path
`max_discovery`	number	No	Max pages to discover (default: 1000)

Returns: Estimation results

{
  "estimated_pages": 230,
  "discovery_rate": 1.28,
  "estimated_time_minutes": 3.8
}

Example:

# Natural language
"Estimate pages for the React config"
"How many pages will Django docs have?"
"Estimate with max 500 pages"

scrape_docs

Scrape documentation website and generate skill.

Parameters:

Name	Type	Required	Description
`config`	object/string	Yes	Config object or file path
`enhance_level`	number	No	0-3 (default: 2)
`max_pages`	number	No	Override max pages
`dry_run`	boolean	No	Preview only

Returns: Scraping results

{
  "skill_directory": "output/react/",
  "pages_scraped": 180,
  "references_generated": 12,
  "status": "success"
}

Example:

# Natural language
"Scrape the React documentation"
"Scrape Django with enhancement level 3"
"Do a dry run of the Vue docs scrape"

package_skill

Package skill directory into uploadable format.

Parameters:

Name	Type	Required	Description
`skill_directory`	string	Yes	Path to skill directory
`target`	string	No	Platform (default: claude)
`streaming`	boolean	No	Use streaming mode

Returns: Package info

{
  "package_path": "output/react-claude.zip",
  "platform": "claude",
  "size_bytes": 245760
}

Example:

# Natural language
"Package the React skill for Claude"
"Create a Gemini package for output/django/"
"Package with streaming mode"

upload_skill

Upload skill package to LLM platform.

Parameters:

Name	Type	Required	Description
`package_path`	string	Yes	Path to package file
`target`	string	No	Platform (default: claude)
`api_key`	string	No	Platform API key

Returns: Upload result

{
  "success": true,
  "platform": "claude",
  "skill_id": "skill_abc123"
}

Example:

# Natural language
"Upload the React package to Claude"
"Upload output/django-gemini.tar.gz to Gemini"

enhance_skill

AI-powered enhancement of SKILL.md.

Parameters:

Name	Type	Required	Description
`skill_directory`	string	Yes	Path to skill directory
`mode`	string	No	API or LOCAL (default: auto)
`workflow`	string	No	Workflow preset name

Returns: Enhancement result

{
  "success": true,
  "mode": "LOCAL",
  "skill_md_lines": 450
}

Example:

# Natural language
"Enhance the React skill"
"Enhance with security-focus workflow"
"Run enhancement in API mode"

install_skill

Complete workflow: scrape → enhance → package → upload.

Parameters:

Name	Type	Required	Description
`config`	object/string	Yes	Config object or file path
`target`	string	No	Platform (default: claude)
`enhance`	boolean	No	Enable enhancement (default: true)
`upload`	boolean	No	Auto-upload (default: true)

Returns: Installation result

{
  "success": true,
  "skill_directory": "output/react/",
  "package_path": "output/react-claude.zip",
  "uploaded": true
}

Example:

# Natural language
"Install the React skill"
"Install Django for Gemini with no upload"
"Complete install of the Vue config"

Extended Tools

scrape_github

Scrape GitHub repository.

Parameters:

Name	Type	Required	Description
`repo`	string	Yes	Owner/repo format
`token`	string	No	GitHub token
`name`	string	No	Skill name
`include_issues`	boolean	No	Include issues (default: true)
`include_releases`	boolean	No	Include releases (default: true)

Example:

# Natural language
"Scrape the facebook/react repository"
"Analyze the Django GitHub repo"
"Scrape vercel/next.js with issues"

scrape_pdf

Extract content from PDF file.

Parameters:

Name	Type	Required	Description
`pdf_path`	string	Yes	Path to PDF file
`name`	string	No	Skill name
`enable_ocr`	boolean	No	Enable OCR for scanned PDFs

Example:

# Natural language
"Scrape the manual.pdf file"
"Extract content from API-docs.pdf"
"Process scanned.pdf with OCR"

scrape_codebase

Analyze local codebase.

Parameters:

Name	Type	Required	Description
`directory`	string	Yes	Path to directory
`preset`	string	No	quick/standard/comprehensive
`languages`	array	No	Language filters

Example:

# Natural language
"Analyze the ./my-project directory"
"Scrape this codebase with comprehensive preset"
"Analyze only Python and JavaScript files"

unified_scrape

Multi-source scraping (docs + GitHub + PDF).

Parameters:

Name	Type	Required	Description
`config`	object/string	Yes	Unified config
`merge_mode`	string	No	rule-based or claude-enhanced

Example:

# Natural language
"Run unified scraping with my-config.json"
"Combine docs and GitHub for React"
"Multi-source scrape with claude-enhanced merge"

detect_patterns

Detect code patterns in repository.

Parameters:

Name	Type	Required	Description
`directory`	string	Yes	Path to directory
`pattern_types`	array	No	Types to detect

Returns: Detected patterns

Example:

# Natural language
"Detect patterns in this codebase"
"Find architectural patterns"
"Show me the code patterns"

extract_test_examples

Extract usage examples from test files.

Parameters:

Name	Type	Required	Description
`directory`	string	Yes	Path to test directory
`language`	string	No	Primary language

Returns: Test examples

Example:

# Natural language
"Extract test examples from tests/"
"Get Python test examples"
"Find usage examples in the test suite"

build_how_to_guides

Generate how-to guides from codebase.

Parameters:

Name	Type	Required	Description
`directory`	string	Yes	Path to directory
`topics`	array	No	Specific topics

Returns: Generated guides

Example:

# Natural language
"Build how-to guides for this project"
"Generate guides about authentication"
"Create how-to documentation"

extract_config_patterns

Extract configuration patterns.

Parameters:

Name	Type	Required	Description
`directory`	string	Yes	Path to directory

Returns: Config patterns

Example:

# Natural language
"Extract config patterns from this project"
"Find configuration examples"
"Show me how this project is configured"

detect_conflicts

Find discrepancies between documentation and code.

Parameters:

Name	Type	Required	Description
`docs_source`	string	Yes	Docs config or directory
`code_source`	string	Yes	Code directory or repo

Returns: Conflict report

{
  "conflicts": [
    {
      "type": "api_mismatch",
      "doc_signature": "foo(a, b)",
      "code_signature": "foo(a, b, c=default)"
    }
  ]
}

Example:

# Natural language
"Detect conflicts between docs and code"
"Find discrepancies in React"
"Compare documentation to implementation"

scrape_generic

Scrape content from any of the 10 new source types.

Purpose: A generic entry point that delegates to the appropriate CLI scraper module for: jupyter, html, openapi, asciidoc, pptx, confluence, notion, rss, manpage, chat.

Parameters:

Name	Type	Required	Description
`source_type`	string	Yes	One of: `jupyter`, `html`, `openapi`, `asciidoc`, `pptx`, `confluence`, `notion`, `rss`, `manpage`, `chat`
`name`	string	Yes	Skill name for the output
`path`	string	No	File or directory path (for file-based sources)
`url`	string	No	URL (for URL-based sources like confluence, notion, rss)

Note: Either path or url must be provided depending on the source type.

Source Type → Input Mapping:

Source Type	Typical Input	CLI Flag Used
`jupyter`	`path`	`--notebook`
`html`	`path`	`--html-path`
`openapi`	`path`	`--spec`
`asciidoc`	`path`	`--asciidoc-path`
`pptx`	`path`	`--pptx`
`manpage`	`path`	`--man-path`
`confluence`	`path` or `url`	`--export-path` / `--base-url`
`notion`	`path` or `url`	`--export-path` / `--database-id`
`rss`	`path` or `url`	`--feed-path` / `--feed-url`
`chat`	`path`	`--export-path`

Returns: Scraping results with file paths and statistics

{
  "skill_directory": "output/my-api/",
  "source_type": "openapi",
  "status": "success"
}

Example:

# Natural language
"Scrape the OpenAPI spec at api/openapi.yaml"
"Extract content from my Jupyter notebook analysis.ipynb"
"Process the Confluence export in ./wiki-export/"
"Convert the PowerPoint slides.pptx into a skill"

# Explicit tool call
scrape_generic(source_type="openapi", name="my-api", path="api/openapi.yaml")
scrape_generic(source_type="jupyter", name="ml-tutorial", path="notebooks/tutorial.ipynb")
scrape_generic(source_type="rss", name="blog", url="https://blog.example.com/feed.xml")
scrape_generic(source_type="confluence", name="wiki", path="./confluence-export/")

Config Source Tools

add_config_source

Parameters:

Name	Type	Required	Description
`name`	string	Yes	Source name
`url`	string	Yes	Git repository URL
`branch`	string	No	Git branch (default: main)

Example:

# Natural language
"Add my-configs repo as a source"
"Register https://github.com/org/configs as configs"

list_config_sources

List all registered config sources.

Parameters: None

Returns: List of sources

Example:

# Natural language
"List my config sources"
"Show registered sources"

remove_config_source

Remove a config source.

Parameters:

Name	Type	Required	Description
`name`	string	Yes	Source name

Example:

# Natural language
"Remove the configs source"
"Delete my old config source"

fetch_config

Fetch configs from a git source.

Parameters:

Name	Type	Required	Description
`source`	string	Yes	Source name
`config_name`	string	No	Specific config to fetch

Example:

# Natural language
"Fetch configs from my source"
"Get the react config from configs source"

submit_config

Submit a config to a source.

Parameters:

Name	Type	Required	Description
`source`	string	Yes	Source name
`config_path`	string	Yes	Path to config file

Example:

# Natural language
"Submit my-config.json to configs source"
"Add this config to my source"

Config Splitting Tools

split_config

Split large configuration into smaller chunks.

Parameters:

Name	Type	Required	Description
`config`	string	Yes	Config file path
`max_pages_per_chunk`	number	No	Pages per chunk (default: 100)
`output_dir`	string	No	Output directory

Example:

# Natural language
"Split the large config into chunks"
"Break up this 500-page config"
"Split with 50 pages per chunk"

generate_router

Generate a router skill for large documentation.

Parameters:

Name	Type	Required	Description
`config`	string	Yes	Config file path
`output_dir`	string	No	Output directory

Example:

# Natural language
"Generate a router for this large config"
"Create a router skill for Django docs"

Vector Database Tools

export_to_weaviate

Export skill to Weaviate vector database.

Parameters:

Name	Type	Required	Description
`skill_directory`	string	Yes	Path to skill
`weaviate_url`	string	No	Weaviate URL
`class_name`	string	No	Class/collection name

Example:

# Natural language
"Export React skill to Weaviate"
"Send to Weaviate at localhost:8080"

export_to_chroma

Export skill to ChromaDB.

Parameters:

Name	Type	Required	Description
`skill_directory`	string	Yes	Path to skill
`collection_name`	string	No	Collection name
`persist_directory`	string	No	Storage directory

Example:

# Natural language
"Export to ChromaDB"
"Send Django skill to Chroma"

export_to_faiss

Export skill to FAISS index.

Parameters:

Name	Type	Required	Description
`skill_directory`	string	Yes	Path to skill
`output_path`	string	No	Index file path

Example:

# Natural language
"Export to FAISS index"
"Create FAISS index for this skill"

export_to_qdrant

Export skill to Qdrant.

Parameters:

Name	Type	Required	Description
`skill_directory`	string	Yes	Path to skill
`collection_name`	string	No	Collection name
`qdrant_url`	string	No	Qdrant URL

Example:

# Natural language
"Export to Qdrant"
"Send skill to Qdrant vector DB"

Workflow Tools

list_workflows

List all available workflow presets.

Parameters: None

Returns:

{
  "workflows": [
    {"name": "security-focus", "source": "bundled"},
    {"name": "my-custom", "source": "user"}
  ]
}

Example:

# Natural language
"List available workflows"
"What workflow presets do I have?"

get_workflow

Get full YAML content of a workflow.

Parameters:

Name	Type	Required	Description
`name`	string	Yes	Workflow name

Returns: Workflow YAML

Example:

# Natural language
"Show me the security-focus workflow"
"Get the YAML for the default workflow"

create_workflow

Create a new workflow.

Parameters:

Name	Type	Required	Description
`name`	string	Yes	Workflow name
`yaml_content`	string	Yes	Workflow YAML

Example:

# Natural language
"Create a workflow called my-workflow"
"Save this YAML as a new workflow"

update_workflow

Update an existing workflow.

Parameters:

Name	Type	Required	Description
`name`	string	Yes	Workflow name
`yaml_content`	string	Yes	New YAML content

Example:

# Natural language
"Update my-custom workflow"
"Modify the security-focus workflow"

delete_workflow

Delete a user workflow.

Parameters:

Name	Type	Required	Description
`name`	string	Yes	Workflow name

Example:

# Natural language
"Delete my-old-workflow"
"Remove the test workflow"

Common Patterns

Pattern 1: Quick Documentation Skill

# Natural language sequence:
"List available configs"
"Scrape the react config"
"Package output/react for Claude"

Tools: list_configs → scrape_docs → package_skill

Pattern 2: GitHub Repository Analysis

# Natural language sequence:
"Scrape the facebook/react GitHub repo"
"Enhance the output/react skill"
"Package it for Gemini"

Tools: scrape_github → enhance_skill → package_skill

Pattern 3: Complete One-Command

# Natural language:
"Install the Django skill for Claude"

Tool: install_skill

Pattern 4: Multi-Source with Workflows

# Natural language sequence:
"List available workflows"
"Run unified scrape with my-unified.json"
"Apply security-focus and api-documentation workflows"
"Package for Claude"

Tools: list_workflows → unified_scrape → enhance_skill → package_skill

Pattern 5: New Source Type Scraping

# Natural language sequence:
"Scrape the OpenAPI spec at api/openapi.yaml"
"Package the output for Claude"

Tools: scrape_generic → package_skill

Pattern 6: Vector Database Export

# Natural language sequence:
"Scrape the Django documentation"
"Export to ChromaDB"

Tools: scrape_docs → export_to_chroma

Error Handling

Common Errors

Error	Cause	Solution
`ConfigNotFoundError`	Config doesn't exist	Check config name or path
`InvalidConfigError`	Config malformed	Use `validate_config`
`ScrapingError`	Network or selector issue	Check URL and selectors
`RateLimitError`	Too many requests	Wait or use token
`EnhancementError`	AI enhancement failed	Check API key or Claude Code

Error Response Format

{
  "error": true,
  "error_type": "ConfigNotFoundError",
  "message": "Config 'react' not found",
  "suggestion": "Run list_configs to see available configs"
}