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Observee (YC S25) lets you build AI agents with 1000+ integrations using MCPs with managed OAuth, Security and Observability

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⭐ If you like Observee, please star us on GitHub!

Observee SDK

The complete Observee SDK - All-in-one package for using MCPs with AI agents, authentication management for MCPs, and complete observability for MCP Builders.

Available for both TypeScript/JavaScript and Python.

What's Included

This SDK includes all Observee components:

  • πŸ€– Agents - MCP tool integration with LLM providers (npm | pypi)
  • πŸ” Auth - OAuth authentication for 15+ services (npm | pypi)
  • πŸ“Š Logger - Structured logging and monitoring (npm | pypi)

Quick Start

TypeScript/JavaScript

# Install everything at once npm install @observee/sdk # Or install individual packages npm install @observee/agents @observee/auth @observee/logger

Python

# Install individual packages (no meta-package yet) pip install mcp-agents agent-oauth mcp-logger # Or install all at once pip install observee

Usage Examples

TypeScript/JavaScript

Option 1: Import from main package

import { chatWithTools, callMcpAuthLogin, Logger } from "@observee/sdk"; // Use agents const result = await chatWithTools("Search for news", { provider: "anthropic", observeeApiKey: "obs_your_key", }); // Use auth const authResponse = await callMcpAuthLogin({ authServer: "gmail", }); // Use logger const logger = new Logger({ apiKey: "obs_your_key" }); logger.info("Application started");

Option 2: Import from specific sub-packages

import { chatWithTools } from "@observee/agents"; import { callMcpAuthLogin } from "@observee/auth"; import { Logger } from "@observee/logger";

Python

from observee_agents import chat_with_tools from observee_auth import call_mcpauth_login # Use agents result = chat_with_tools( "Search for news", provider="anthropic", observee_api_key="obs_your_key" ) # Use auth auth_response = call_mcpauth_login(auth_server="gmail") print(f"Login URL: {auth_response['auth_url']}")

Complete Example

TypeScript/JavaScript

import { chatWithTools, callMcpAuthLogin, Logger } from "@observee/sdk"; // Set up logging const logger = new Logger({ apiKey: "obs_your_key", service: "my-app", }); async function main() { try { // Authenticate with Gmail logger.info("Starting Gmail authentication"); const auth = await callMcpAuthLogin({ authServer: "gmail", }); console.log("Visit:", auth.url); // Use AI agent with tools logger.info("Starting AI chat with tools"); const result = await chatWithTools("Search my emails for project updates", { provider: "anthropic", observeeApiKey: "obs_your_key", }); console.log("AI Response:", result.content); logger.info("AI chat completed", { toolsUsed: result.toolCalls?.length || 0, }); } catch (error) { logger.error("Application error", { error: error.message }); } } main();

Python

from observee_agents import chat_with_tools call_mcpauth_login import asyncio async def main(): try: # Authenticate with Gmail logger.info("Starting Gmail authentication") auth = call_mcpauth_login(auth_server="gmail") print(f"Visit: {auth['auth_url']}") # Use AI agent with tools logger.info("Starting AI chat with tools") result = await chat_with_tools( "Search my emails for project updates", provider="anthropic", observee_api_key="obs_your_key" ) print(f"AI Response: {result['content']}") except Exception as error: logger.error("Application error", {"error": str(error)}) # Run the async function asyncio.run(main())

Features Overview

πŸ€– AI Agents

  • Multi-Provider Support: Anthropic Claude, OpenAI GPT, Google Gemini
  • MCP Tool Integration: 15+ pre-built tools (Gmail, YouTube, Linear, etc.)
  • Smart Filtering: BM25, local embeddings, cloud-based filtering
  • Streaming Support: Real-time responses
  • Conversation Memory: Persistent chat history

πŸ” Authentication

  • OAuth 2.0 Flows: Gmail, Slack, Notion, Linear, GitHub, and more
  • Simple Integration: One-line authentication
  • Secure Token Management: Automatic storage and refresh
  • Custom Redirects: Support for self-hosted servers

πŸ“Š Logging

  • Structured Logging: JSON-based log format
  • Usage Tracking: Monitor API usage and costs
  • Multiple Transports: Console, file, and cloud logging
  • Performance Monitoring: Track response times and errors

Support

Citation

If you use Observee in your research or project, please cite:

@software{observee, title={Observee}, author={observee-ai}, year={2025}, publisher = {GitHub}, url={https://github.com/observee-ai/observee} }

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