How do I get my Outreach API credentials?

Go to the **Outreach Developer Portal** at **developers.outreach.io** and log in with your Outreach account. Navigate to **My Apps** and click **Create New App**. Provide a name, description, and configure the **Redirect URI** and required **scopes** (e.g., `read_prospects`, `write_prospects`). After saving, you'll receive your **Client ID** and **Client Secret**. Copy both and paste them into the configuration fields below. Note: Outreach generates both development and production credentials —

Can my AI agent tell me which sequences are performing best?

Yes. Ask your agent to compare sequences by reply rate, open rate, or meeting booked rate and it returns a ranked list — helping you double down on what works and kill underperforming sequences before they damage your domain reputation.

What if I need to check team activity quickly during standup?

Ask your AI agent 'What did my team do yesterday?' and get a summary of emails sent, calls made, replies received, and meetings booked per rep — perfect for 30-second standup updates without pulling up dashboards.

Is this suitable for large enterprise SDR teams?

Absolutely. Outreach is built for enterprise sales organizations with hundreds of reps. Your AI agent queries the same API used by Outreach's native platform — supporting team-level views, advanced filtering, and role-based access controls.

Outreach MCP Server for Pydantic AI 8 tools — connect in under 2 minutes

Name: Outreach
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 8 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Outreach through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to Outreach "
            "(8 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Outreach?"
    )
    print(result.data)

asyncio.run(main())

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* 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 Outreach MCP Server

Connect Outreach to your AI agent and manage your enterprise sales engagement platform conversationally.

Pydantic AI validates every Outreach tool response against typed schemas, catching data inconsistencies at build time. Connect 8 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.

What you can do

Prospect Management — Search, create, and update prospect records with contact information, tags, and engagement history.
Sequence Tracking — List active sequences, check enrollment statuses, and monitor step completion rates.
Email Analytics — Pull open rates, reply rates, bounce rates, and click metrics across sequences and campaigns.
Activity Feed — Query recent calls, emails, and tasks across your SDR team for pipeline visibility.

The Outreach MCP Server exposes 8 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Outreach to Pydantic AI via MCP

Follow these steps to integrate the Outreach MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 8 tools from Outreach with type-safe schemas

Why Use Pydantic AI with the Outreach MCP Server

Pydantic AI provides unique advantages when paired with Outreach through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Outreach integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your Outreach connection logic from agent behavior for testable, maintainable code

Outreach + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Outreach MCP Server delivers measurable value.

Type-safe data pipelines: query Outreach with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Outreach tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Outreach and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Outreach responses and write comprehensive agent tests

Outreach MCP Tools for Pydantic AI (8)

These 8 tools become available when you connect Outreach to Pydantic AI via MCP:

get_outreach_prospect

Get details for a specific prospect

get_outreach_sequence_stats

Get engagement metrics for a sequence

list_outreach_accounts

List company accounts

list_outreach_emails

List email addresses linked to prospects

list_outreach_mailboxes

List connected sending mailboxes

list_outreach_prospects

List sales prospects

list_outreach_sequences

List automated outreach sequences

list_outreach_tasks

List sales tasks

Example Prompts for Outreach in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Outreach immediately.

"How are my active sequences performing?"

"Search for prospect 'David Kim' in Outreach."

"What did my SDR team accomplish yesterday?"

Troubleshooting Outreach MCP Server with Pydantic AI

Common issues when connecting Outreach to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Outreach + Pydantic AI FAQ

Common questions about integrating Outreach MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your Outreach MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.