How to Use the Currents MCP in Pydantic AI
Type-safe news retrieval for your agents using Currents and Pydantic AI.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Currents MCP to Pydantic AI
Create your Vinkius account to connect Currents to Pydantic AI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.
Type-safe news feeds with Pydantic AI
The `get_latest_news` tool fetches breaking articles while your framework guarantees the data structure. You define exactly what fields the agent expects to receive. The API returns real-time updates from global sources. If the news provider changes their payload, your agent fails loudly with a runtime validation error. There is no silent corruption or hallucinated text creeping into your application. You know exactly what data you are working with before the agent processes it.
Search archives across any LLM
Using `search_news` gives your agent the ability to run keyword and boolean queries against a massive article database. The agent constructs the search parameters based on user prompts. It pulls historical data to answer specific research questions. Because this framework is model-agnostic, you can swap out the underlying LLM at any time. You might use a local model for drafting the search queries and Anthropic for summarizing the results. The MCP Server works identically regardless of which brain powers the agent.
Discover categories via the Currents MCP Server
The `list_categories` and `list_regions` tools provide the exact constraints your agent needs to build valid requests. It reads the supported news topics directly from the source. The agent never guesses which categories exist. This dynamic discovery pairs perfectly with strict typing. The agent pulls the valid regions, validates them against your internal models, and then executes a perfectly formatted search. You eliminate bad requests before they ever hit the network.
Set up Currents MCP in Pydantic AI
Prerequisites
- Python 3.10+ installed
-
pydantic-ai-slim[fastmcp]package - Active Vinkius subscription with a valid endpoint token
- 1
Install Pydantic AI with FastMCP
Run
pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecatedMCPServerHTTPclass with full protocol support. - 2
Configure the FastMCPToolset
Pass a JSON-style config dict to
FastMCPToolsetwith your Vinkius URL. Replace[YOUR_TOKEN_HERE]with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports. - 3
Create and run your agent
Pass the toolset to
Agent(toolsets=[toolset])and callagent.run(). Swapopenai:gpt-4ofor any supported model — Anthropic, Google, Mistral, or Groq.
from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset
toolset = FastMCPToolset({
"mcpServers": {
"currents-mcp": {
"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
}
}
})
agent = Agent(
"openai:gpt-4o",
toolsets=[toolset],
system_prompt="You have access to Currents tools.",
)
result = await agent.run("List recent Currents transactions")
print(result.output) Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Currents. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
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Common questions about Currents MCP in Pydantic AI
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