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context-space

context-space · context-space/context-space

Offers unified MCP tools and secure integrations to help AI agents interact effectively with real-world services and data, turning context engineering into practice.

Ultimate Context Engineering Infrastructure, starting from MCPs and Integrations

813 stars82License: AGPL-3.0Updated 12 months ago0 opens

Preview

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What you can do with it

  • Connect your AI agents to various real-world services through secure, standardized integrations.
  • Enable agents to access live data and tools that are otherwise scattered across inconsistent APIs.
  • Build automation workflows for AI agents that require interacting with external systems.

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From the README

Context Space: The First Context Engineering Infrastructure to 10× Your Productivity

English | 中文

Context Space offers unified MCP tools, secure & verified integrations, and a 5-minute setup — perfect for AI agents, automation workflows, and developer tools. As the first context engineering infrastructure, it turns theory into practice by delivering better context and enabling agents to interact effectively with the real world.

Our Vision

Today's Al agents excel at reasoning but terrible at acting in the real world. They’re cut off from live data and tools, trapped behind scattered APIs, inconsistent sources, and complex authentication..

Context Space changes this. It packages core agent capabilities like task orchestration and memory into standardized, callable tools. With built-in tool discovery and recommendation, it gives agents a clear, controllable, and interpretable path to invoke real-world context.

Context Space makes AI agents truly usable. By combining enterprise-grade security with zero-config simplicity, we are building tool-first context engineering infrastructure that enable agents to seamlessly and securely interact with any service or data source.

Start Context Engineering with Context Space

Context engineering is the foundation for building reliable AI agents. It goes beyond prompt engineering by managing not only what users say to the model, but also the broader context that shapes its behavior, such as tools, memory, and data.

MCP defines a standard path for agents to securely access real-world services. Context Space brings that vision to life by turning MCP into production-ready infrastructure.

Today, Context Space delivers a secure integration layer with persistent credential management. Guided by MCP principles, it’s evolving into a complete context engineering platform for the next generation of AI.

🚀 One-Click AI Integration

Transform your AI assistant into a powerful agent in seconds.

Cursor IDE - One-click install via cursor:// deep links. Click "Add to Cursor" and instantly give Claude access to GitHub, Slack, Notion, and 38+ services without editing any JSON files.

Claude Code - Simple CLI integration:

claude mcp add "context-space" https://api.context.space/api/mcp --header "Authorization: Bearer YOUR_API_KEY"

Live Demo

1️⃣ OAuth Flow in Action

Simple OAuth setup - no more config file editing

2️⃣ Star a GitHub Repository

GitHub integration - Star repositories with natural language

3️⃣ Web Search

Real-time web search - get the latest information instantly

Try Live: https://context.space/integrations


Roadmap: From Foundation to Frontier

Our development is structured in clear phases, evolving from the robust production foundation available today to the intelligent context engine of tomorrow.

1️⃣ Phase 1: Production-Ready Foundation (Available Now)

The initial phase solves the most critical challenges of using context protocols in production environments, delivering a stable, secure, and scalable infrastructure.

Challenge in ProductionThe Context Space Solution
Manual, Insecure Credential Handling**One-Click OAuth & Vault Security:**Connect to 14+ services with secure OAuth flows, backed by HashiCorp Vault for enterprise-grade credential management.
Inconsistent and Complex APIs**A Single, Unified RESTful API:**Interact with all services through one clean, consistent, and reliable API that you'll actually enjoy using.
Complex Deployment & Scattered MCP Servers**Unified Context Plane with Tool Aggregation:**Connect once, and access everything. Manage all capabilities from a single mcp server endpoint.

2️⃣ Phase 2: The Intelligent Context Layer ( In Development)

Building on this foundation, our future work focuses on enabling more advanced AI capabilities.

Roadmap Timeline:

TimelineKey FeaturesMCP Integration
Next 6 monthsNative MCP Support, Context Memory, Smart AggregationFull MCP protocol compatibility
6-12 monthsSemantic Retrieval, Context Optimization, Real-time UpdatesEnhanced MCP tool capabilities
12+ monthsContext Synthesis, Predictive Loading, AI Context ReasoningAdvanced MCP ecosystem features

Supported Services & Context Sources

Production-Ready Integrations

ServiceCategoryAuthContext CapabilitiesStatus
GitHubDevelopmentOAuthCode repos, issues, PRs, commit historyReady
SlackCommunicationOAuthTeam conversations, channels, workflowsReady
AirtableData ManagementOAuthStructured business data, CRM recordsReady
HubSpotCRMOAuthCustomer data, sales pipeline, interactionsReady
NotionKnowledgeOAuthDocumentation, project plans, wikisReady
SpotifyPersonalOAuthMusic preferences, listening patternsReady
StripeFinancialAPI KeyPayment data, customer behaviorReady
More...VariousVarious5+ additional integrationsReady

✅ 14+ integrations ready to use • More being added weekly

View All Integrations →


📖 API Documentation

Quick API Examples

🔐 Authentication

curl -H "Authorization: Bearer <jwt-token>" \
     https://api.context.space/v1/users/me

🔗 Create OAuth Authorization URL

curl -H "Authorization: Bearer <jwt-token>" \
     -X POST \
     https://api.context.space/v1/credentials/auth/oauth/github/auth-url

⚡ Execute Operations

curl -H "Authorization: Bearer <jwt-token>" \
     -X POST \
     https://api.context.space/v1/invocations/github/list_repositories

Complete API Documentation:

View source on GitHub