Overview

This repository contains a collection of purpose-built Model Context Protocol servers, each designed around a specific capability: web scraping and structured data extraction, codebase navigation and analysis, LLM-powered text generation, and JSON querying. Every server exposes its functionality as MCP tools and resources, making them composable building blocks for AI agent workflows.

The servers span two language ecosystems — TypeScript for the Firecrawl integration and DeepSeek/JSON servers, Python for the codebase analysis server — and follow the MCP SDK conventions for tool definitions, resource URIs, and transport configuration (stdio and HTTP).

Technology Stack

Languages
MCP Framework
Web Scraping
AI Integration
Data & Querying
Runtime
Tooling

Server Index

Server	Language	Transport	Tools	Resources	Description
Firecrawl Web Scraping	TypeScript	stdio	10	—	Web scraping, crawling, batch processing, LLM extraction, deep research, and cannabis strain data extraction
Codebase Analysis	Python	stdio	6	4	File system navigation, code search, project structure analysis, and real-time change monitoring
DeepSeek R1	JavaScript	stdio	5	5	Text generation, summarization, streaming, multi-model support, and document processing via DeepSeek AI
JSON Manager	JavaScript	stdio / HTTP	4	4	JSONPath querying, advanced filtering, dataset comparison, and result caching

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Firecrawl Web Scraping Server

A comprehensive MCP server built on the Firecrawl platform for web scraping, content extraction, and structured data collection. Extends the base Firecrawl capabilities with a specialized cannabis strain data extraction pipeline that collects 66 standardized data points per strain from Leafly.com using dual extraction strategies: regex-based pattern matching and LLM-powered schema extraction.

Tools

Tool	Description
firecrawl_scrape	Scrape a single page with format selection (markdown, HTML, screenshots), custom actions, and content filtering
firecrawl_map	Discover all URLs on a website and generate a site map
firecrawl_crawl	Recursively crawl a website with depth and page limits
firecrawl_batch_scrape	Scrape multiple URLs concurrently with queue-based processing
firecrawl_check_batch_status	Poll the status of an in-progress batch scrape job
firecrawl_check_crawl_status	Poll the status of an in-progress crawl job
firecrawl_search	Search the web and return scraped content from results
firecrawl_extract	LLM-powered structured data extraction using a caller-defined JSON schema
firecrawl_deep_research	Multi-step research workflow that scrapes, synthesizes, and reports on a topic
firecrawl_leafly_strain	Extract standardized cannabis strain data (cannabinoids, terpenes, effects, flavors, interactions)

Strain Data Extraction Pipeline

The Leafly strain extractor is the most specialized component in this collection. It implements two complementary extraction strategies against the same data source:

Regex-based extraction parses raw HTML/markdown content with pattern-matching rules for cannabinoid percentages, terpene profiles, effect ratings, and flavor descriptors. This approach is deterministic and fast, but brittle against layout changes.

LLM-powered extraction uses Firecrawl's extract endpoint to send page content to an LLM with a structured JSON schema. This approach handles unstructured text, formatting variations, and missing data more gracefully, at the cost of API latency and token usage.

Both strategies normalize output to a consistent schema covering:

Category	Fields
Cannabinoids	THC, CBD, CBG, CBN
Terpenes	Myrcene, Pinene, Caryophyllene, Limonene, Linalool, Terpinolene, Ocimene, Humulene
Medical Effects	Stress, Anxiety, Depression, Pain, Insomnia, Lack of Appetite, Nausea
User Effects	Happy, Euphoric, Creative, Relaxed, Uplifted, Energetic, Focused, Sleepy, Hungry, Talkative, Tingly, Giggly
Adverse Effects	Dry Mouth, Dry Eyes, Dizzy, Paranoid, Anxious
Flavors	Berry, Sweet, Earthy, Pungent, Pine, Vanilla, Minty, Skunky, Citrus, Spicy, Herbal, Diesel, Tropical, Fruity, Grape
Pharmacokinetics	Onset (minutes), Duration (hours)
Drug Interactions	Sedatives, Benzodiazepines, SSRIs, Opioid Analgesics, Anticonvulsants, Anticoagulants

Normalization methodology: lab-tested data is prioritized. When exact values are unavailable, standardized normalization is applied (dominant terpene = 0.008, second = 0.005, third = 0.003). Effects and flavors are normalized to a 0.0–1.0 scale.

Quick Start

cd firecrawl-mcp-server
npm install
cp .env.example .env          # Add your FIRECRAWL_API_KEY
npm run build
npm start                     # Start the MCP server (stdio transport)

# CLI: extract strain data directly
npm run scrape-leafly -- output.csv "Blue Dream,OG Kush,Sour Diesel"

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Codebase Analysis Server

A Python MCP server for navigating and analyzing codebases. Provides file system access, text search, function discovery, dependency analysis, and real-time file change monitoring via watchdog. Built with the Python MCP SDK's FastMCP framework.

Tools

Tool	Description
search_function	Find function definitions across Python, JavaScript, and TypeScript files
search_code	Full-text search across all code files in a directory tree
get_project_structure	Generate a tree-view representation of the project directory
analyze_dependencies	Parse and analyze project dependency manifests
find_components	Discover React and React Native component definitions

Resources

URI	Description
file/list/{directory}	List files in a directory
file/read/{filepath}	Read file contents (with LRU caching)
file/info/{filepath}	Get file metadata (size, timestamps)
file/changes/{directory}	Get recently modified files (watchdog-backed)

Quick Start

cd Model-Context-Protocol-servers
pip install "mcp[cli]" watchdog
python code_server.py

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DeepSeek R1 Server

An MCP server that integrates with DeepSeek AI models for text generation, summarization, streaming output, and document processing. Supports multiple DeepSeek models (Reasoner, Chat, Coder) through the OpenAI-compatible API. Includes an in-memory response cache and file persistence for generated outputs.

Tools

Tool	Description
deepseek_r1	Generate text using the DeepSeek Reasoner model (optimized for complex reasoning)
deepseek_summarize	Condense text into a summary
deepseek_stream	Stream text generation with chunked output
deepseek_multi	Generate text using a caller-specified DeepSeek model variant
deepseek_document	Process documents: summarize, extract entities, or analyze sentiment

Resources

URI	Description
model/info	Supported models, context lengths, and capabilities
server/status	Server health and uptime status
file/save/{filename}	Persist generated content to disk
file/list	List previously saved output files
file/read/{filename}	Read a saved output file

Supported Models

Model	Context	Optimized For
DeepSeek-Reasoner (R1)	8K tokens	Complex reasoning, math, code
DeepSeek-Chat (V3)	8K tokens	General conversation and knowledge
DeepSeek-Coder	16K tokens	Code generation, debugging, explanation

Quick Start

cd Model-Context-Protocol-servers
echo "DEEPSEEK_API_KEY=your_key_here" > .env
npm install @modelcontextprotocol/sdk openai dotenv
node deepseek.py                # Starts on stdio transport

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JSON Manager Server

An MCP server for querying, filtering, comparing, and caching JSON data. Uses JSONPath expressions for traversal, supports advanced filtering with string, numeric, and date operations, and provides persistent query storage. Supports both stdio and HTTP transports.

Tools

Tool	Description
query	Query JSON data using JSONPath expressions with array operations
filter	Filter JSON arrays by field conditions (equality, range, pattern matching)
save_query	Persist query results to disk for later retrieval
compare_json	Diff two JSON datasets and report structural/value differences

Resources

URI	Description
saved_queries/list	List all saved query result files
saved_queries/get/{filename}	Retrieve a previously saved query result
cache/status	Cache size, TTL configuration, and entry ages
cache/clear	Flush the in-memory query cache

Quick Start

cd Model-Context-Protocol-servers
npm install @modelcontextprotocol/sdk node-fetch jsonpath
node json.py                          # stdio transport (default)
node json.py --port=3000              # HTTP transport

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Project Structure

.
├── firecrawl-mcp-server/                  # TypeScript — Firecrawl + Leafly MCP server
│   ├── src/
│   │   ├── index.ts                       # MCP server entry point (10 tools)
│   │   ├── leafly-scraper.ts              # Strain data extraction engine
│   │   ├── leafly-scraper-cli.ts          # CLI interface for direct scraping
│   │   └── index.test.ts                  # Jest test suite
│   ├── leafly-extract-data/               # Extracted strain datasets (batches + individual)
│   ├── leafly-analysis/                   # Raw HTML analysis of strain pages
│   ├── extract-test-output/               # Sample extraction results
│   ├── Dockerfile                         # Container build
│   ├── package.json
│   └── tsconfig.json
│
├── Model-Context-Protocol-servers/        # Python + JavaScript MCP servers
│   ├── code_server.py                     # Codebase analysis server (Python, FastMCP)
│   ├── deepseek.py                        # DeepSeek R1 server (JavaScript, FastMCP)
│   ├── json.py                            # JSON manager server (JavaScript, FastMCP)
│   ├── main.py                            # Python entry point
│   └── pyproject.toml                     # Python project configuration
│
├── terminal-top-panel.svg                 # README header graphic
├── terminal-bottom-panel.svg              # README footer graphic
└── README.md

Getting Started

Prerequisites

• Node.js 18+ for the Firecrawl, DeepSeek, and JSON servers
• Python 3.12+ for the codebase analysis server
• Firecrawl API key for the web scraping server (obtain from firecrawl.dev)
• DeepSeek API key for the DeepSeek R1 server (obtain from deepseek.com)

Installation

# Clone the repository
git clone https://github.com/adi2355/MCP-Server-Collection.git
cd MCP-Server-Collection

# Firecrawl server
cd firecrawl-mcp-server && npm install && npm run build && cd ..

# Python codebase server
cd Model-Context-Protocol-servers && pip install "mcp[cli]" watchdog && cd ..

Environment Variables

Variable	Server	Required
FIRECRAWL_API_KEY	Firecrawl Web Scraping	Yes
DEEPSEEK_API_KEY	DeepSeek R1	Yes

License

MIT License