Stanford GDELT MCP Server for AutoGenGive AutoGen instant access to 16 tools to Get Geo Data, Get Themes, Get Timeline Country, and more
GDPR Free for SubscribersMicrosoft AutoGen enables multi-agent conversations where agents negotiate, delegate, and execute tasks collaboratively. Add Stanford GDELT as an MCP tool provider through Vinkius and every agent in the group can access live data and take action.
Ask AI about this MCP Server for AutoGen
The Stanford GDELT MCP Server for AutoGen is a standout in the Data Analytics category — giving your AI agent 16 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
Geminiimport asyncio
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.tools.mcp import McpWorkbench
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
async with McpWorkbench(
server_params={"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"},
transport="streamable_http",
) as workbench:
tools = await workbench.list_tools()
agent = AssistantAgent(
name="stanford_gdelt_agent",
tools=tools,
system_message=(
"You help users with Stanford GDELT. "
"16 tools available."
),
)
print(f"Agent ready with {len(tools)} tools")
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Stanford GDELT MCP Server
Connect to the GDELT Project API — the world's largest open platform for monitoring global news media in real time.
AutoGen enables multi-agent conversations where agents negotiate, delegate, and collaboratively use Stanford GDELT tools. Connect 16 tools through Vinkius and assign role-based access. a data analyst queries while a reviewer validates, with optional human-in-the-loop approval for sensitive operations.
What you can do
- Article Search — Search global news articles with filters for language, country, date range, and topic
- Volume Timelines — Track how media attention to any topic changes over time
- Sentiment Analysis — Monitor tone and sentiment shifts in coverage of any subject
- Geographic Mapping — Visualize where news events are happening around the world
- TV News Search — Search closed caption transcripts from CNN, Fox News, MSNBC, BBC, and more
- Theme Analysis — Explore standardized GDELT themes across geopolitics, health, environment, and economics
- Language Distribution — See which linguistic communities are covering a topic
- Country Distribution — Identify which nations produce the most coverage of specific issues
- Proximity Search — Find articles where two terms appear near each other
- Word Clouds — Extract dominant terms and concepts from coverage
The Stanford GDELT MCP Server exposes 16 tools through the Vinkius. Connect it to AutoGen in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
All 16 Stanford GDELT tools available for AutoGen
When AutoGen connects to Stanford GDELT through Vinkius, your AI agent gets direct access to every tool listed below — spanning gdelt, global-news, sentiment-analysis, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.
Get geo data on Stanford GDELT
Each point includes coordinates, location name, and article metadata. Use modes: "PointData" for individual points, "PointHeat" for heatmap data. Get geographic point data for news events
Get themes on Stanford GDELT
GDELT uses hundreds of themes from politics, economics, health, environment, technology, and more to classify news content. Get GDELT theme distribution for a topic
Get timeline country on Stanford GDELT
Reveals geographic patterns in media attention, identifies when a story goes global, and shows which nations are most interested in specific issues. Get source country distribution timeline
Get timeline lang on Stanford GDELT
Reveals which linguistic communities are paying attention to an issue and when interest spreads across language barriers. Get language distribution timeline for a topic
Get timeline tone on Stanford GDELT
Positive values indicate positive coverage, negative values indicate negative coverage. Essential for tracking public opinion shifts, crisis communications, and brand reputation monitoring. Get sentiment and tone timeline for a topic
Get timeline volume on Stanford GDELT
Essential for tracking media attention, identifying news spikes, and understanding the lifecycle of a story. Default timespan is 3 months. Get news volume timeline for any topic
Get tone chart on Stanford GDELT
Shows whether coverage is predominantly positive, negative, or neutral, and the overall emotional intensity of the coverage. Get tone distribution chart for a topic
Get tv channels on Stanford GDELT
Use this to understand the scope of TV news coverage available for analysis. Get available TV news channels inventory
Get tv timeline on Stanford GDELT
Reveals which stories dominate TV airtime and how TV coverage patterns differ from online news. Get TV news mention volume timeline
Get word cloud on Stanford GDELT
Reveals the dominant themes, entities, and concepts associated with a topic in media discourse. Get word cloud data showing key terms for a topic
Search articles on Stanford GDELT
Returns article titles, URLs, dates, source domains, languages, and source countries. Use timespan like "1d" (1 day), "1w" (1 week), "3m" (3 months). Use sourcelang codes like "english", "spanish", "portuguese", "french", "chinese", "arabic". Use sourcecountry codes like "US", "BR", "UK", "FR", "DE". Search global news articles across 100+ languages
Search by country on Stanford GDELT
Country codes follow ISO 2-letter format: US (United States), BR (Brazil), UK (United Kingdom), FR (France), DE (Germany), CN (China), JP (Japan), IN (India), RU (Russia), AU (Australia), CA (Canada), etc. Essential for understanding country-specific media perspectives on global events. Search news articles from a specific country
Search by language on Stanford GDELT
Covers 100+ languages. Language codes include: english, spanish, portuguese, french, german, italian, chinese, japanese, korean, arabic, russian, hindi, turkish, dutch, swedish, polish, and many more. Essential for monitoring how different linguistic communities cover the same event. Search news articles in a specific language
Search by theme on Stanford GDELT
Themes are standardized topic categories like TAX_FNCACT (financial actions), HEALTH_PANDEMIC, ENV_CLIMATECHANGE, TERROR, PROTEST, ELECTION, ECON_BANKRUPTCY, etc. Use this for precise topic-based monitoring. Search articles by GDELT standardized theme
Search nearby on Stanford GDELT
More precise than simple keyword search. Use distance parameter to control proximity (default 10 words). Example: term1="climate", term2="migration", distance=15. Search articles where two terms appear near each other
Search tv on Stanford GDELT
Returns clips with timestamps, station names, transcript snippets, and video preview URLs. Covers CNN, Fox News, MSNBC, BBC, and more. Modes: "ClipGallery" for clips, "StationChart" for station comparison. Search TV news transcripts by keyword
Connect Stanford GDELT to AutoGen via MCP
Follow these steps to wire Stanford GDELT into AutoGen. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.
Install AutoGen
pip install "autogen-ext[mcp]"Replace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenIntegrate into workflow
Explore tools
Why Use AutoGen with the Stanford GDELT MCP Server
AutoGen provides unique advantages when paired with Stanford GDELT through the Model Context Protocol.
Multi-agent conversations: multiple AutoGen agents discuss, delegate, and collaboratively use Stanford GDELT tools to solve complex tasks
Role-based architecture lets you assign Stanford GDELT tool access to specific agents. a data analyst queries while a reviewer validates
Human-in-the-loop support: agents can pause for human approval before executing sensitive Stanford GDELT tool calls
Code execution sandbox: AutoGen agents can write and run code that processes Stanford GDELT tool responses in an isolated environment
Stanford GDELT + AutoGen Use Cases
Practical scenarios where AutoGen combined with the Stanford GDELT MCP Server delivers measurable value.
Collaborative analysis: one agent queries Stanford GDELT while another validates results and a third generates the final report
Automated review pipelines: a researcher agent fetches data from Stanford GDELT, a critic agent evaluates quality, and a writer produces the output
Interactive planning: agents negotiate task allocation using Stanford GDELT data to make informed decisions about resource distribution
Code generation with live data: an AutoGen coder agent writes scripts that process Stanford GDELT responses in a sandboxed execution environment
Example Prompts for Stanford GDELT in AutoGen
Ready-to-use prompts you can give your AutoGen agent to start working with Stanford GDELT immediately.
"What are the latest news articles about AI regulation?"
"How has sentiment about climate change evolved over the last 3 months?"
"Search for TV news clips mentioning quantum computing"
Troubleshooting Stanford GDELT MCP Server with AutoGen
Common issues when connecting Stanford GDELT to AutoGen through Vinkius, and how to resolve them.
McpWorkbench not found
pip install "autogen-ext[mcp]"Stanford GDELT + AutoGen FAQ
Common questions about integrating Stanford GDELT MCP Server with AutoGen.
How does AutoGen connect to MCP servers?
Can different agents have different MCP tool access?
Does AutoGen support human approval for tool calls?
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