A
licenseA
qualityC
maintenanceEnables LLMs to search for keywords and fetch full page content from Wikipedia across various languages. It provides direct access to Wikipedia information through search and fetch tools.
2
4
MIT
wikipedia-mcp-agent
by sadeghetemad
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@wikipedia-mcp-agentExplain quantum entanglement"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
š Wikipedia MCP Agent
A conversational AI agent that searches and reads Wikipedia using the Model Context Protocol (MCP), LangGraph, and AWS Bedrock (Claude Sonnet).
Overview
This project wires together three modern AI infrastructure pieces:
MCP (Model Context Protocol) ā a standard way to expose tools, prompts, and resources to an LLM
LangGraph ā a graph-based agent framework for multi-step reasoning with tool calls
AWS Bedrock ā managed LLM inference using Anthropic's Claude Sonnet
The agent launches an MCP server as a subprocess, dynamically loads its Wikipedia tools at runtime, and runs a stateful chat loop where the LLM can call tools as needed before answering.
Related MCP server: wikipedia-mcp
Architecture
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ā mcp_client.py ā
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ā ā LangGraph StateGraph ā ā
ā ā ā ā
ā ā START āāāŗ chat_node āāāŗ tool_node āāā ā ā
ā ā ā² ā ā ā
ā ā āāāāāāāāāāāāāāāāāāāāāā ā ā
ā ā ā END ā ā
ā āāāāāāāāāāāāāāāāāāāāāāāāāāā¼āāāāāāāāāāāāāāāāāāāāā ā
ā ā tool calls ā
ā stdin/stdout (MCP stdio transport) ā
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ā mcp_server.py ā
ā ā
ā Tools search_wikipedia ā
ā list_wikipedia_sections ā
ā get_section_content ā
ā ā
ā Prompts highlight_sections_prompt ā
ā ā
ā Resources suggested_titles ā
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wikipedia Python libraryFeatures
Tools
Tool | Description |
| Search Wikipedia and return the summary + URL of the top result |
| List all section titles of a Wikipedia article |
| Fetch the full text of a specific section |
Prompts
Prompt | Description |
| Ask the LLM to pick the 3ā5 most important sections of an article and explain why |
Resources
Resource | Description |
| Reads a local |
Getting Started
Prerequisites
Python 3.10+
AWS account with Bedrock access enabled for
anthropic.claude-sonnet-4-6ineu-west-2
Installation
# Clone the repo
git clone https://github.com/sadeghetemad/wikipedia-mcp-agent.git
cd wikipedia-mcp-agent
# Create and activate a virtual environment
python -m venv venv
venv\Scripts\activate # Windows
# source venv/bin/activate # macOS / Linux
# Install dependencies
pip install -r requirements.txtAWS Credentials
Configure your credentials via the AWS CLI or environment variables:
aws configureOr manually:
export AWS_ACCESS_KEY_ID=your_key
export AWS_SECRET_ACCESS_KEY=your_secret
export AWS_DEFAULT_REGION=eu-west-2Make sure your IAM user/role has the bedrock:InvokeModel permission.
Usage
python mcp_client.pyYou will see:
Wikipedia MCP agent is ready.
Type a question or use one of the slash commands below:
/prompts - list available prompt templates
/prompt <name> "arg1" ... - run a prompt template
/resources - list available resources
/resource <name or index> - view a resource
exit / quit / q - quitExample session
You: What is quantum entanglement?
AI: Quantum entanglement is a physical phenomenon where two or more particles ...
You: /prompts
Available Prompts:
highlight_sections_prompt (topic)
You: /prompt highlight_sections_prompt "Black hole"
=== Prompt Result ===
ā¢ Formation ā explains how black holes arise from stellar collapse
ā¢ Event horizon ā the defining boundary of no return
...
You: /resources
Available Resources:
[1] suggested_titles
You: /resource 1
=== Resource Text ===
Artificial intelligence
Large language model
...Optional: suggested_titles.txt
Create this file in the project root (one topic per line) to populate the suggested_titles resource:
Artificial intelligence
Large language model
Model Context Protocol
Quantum computingProject Structure
wikipedia-mcp-agent/
āāā mcp_server.py # FastMCP server ā tools, prompts, resources
āāā mcp_client.py # LangGraph agent + interactive chat loop
āāā requirements.txt # Pinned Python dependencies
āāā suggested_titles.txt # (optional) topic suggestions for the resource
āāā README.mdTech Stack
Layer | Library |
LLM | AWS Bedrock via |
Agent framework | |
Tool protocol | MCP via |
Wikipedia data |
License
MIT
This server cannot be deployed
Maintenance
ActivityStale
ResponsivenessNo issues
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