skill-seekers-reference/docs/reference/MCP_REFERENCE.md

MCP Reference - Skill Seekers

Version: 3.2.0
Last Updated: 2026-03-15
Complete reference for 27 MCP tools

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Table of Contents

• Overview
  • What is MCP?
  • Transport Modes
  • Starting the Server
• Tool Categories
  • Core Tools (9)
  • Extended Tools (9)
  • Config Source Tools (5)
  • Config Splitting Tools (2)
  • Vector Database Tools (4)
  • Workflow Tools (5)
• Tool Reference
• Common Patterns
• Error Handling

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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

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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_codebase	Local codebase analysis
scrape_generic	Generic scraper for 10 new source types
unified_scrape	Multi-source scraping
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
detect_conflicts	Find doc/code discrepancies

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

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

Register a git repository as a 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

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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"
}

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See Also

• CLI Reference - Command-line interface
• Config Format - JSON configuration
• MCP Setup Guide - Server configuration

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For tool help: Ask the AI agent about specific tools