The most Accurate Context
for your Coding Agent
Token-optimized context—the only tool your coding agent needs.Docs, code, web, deep research integrated.
major frameworks and languages.
what you need—no more, no less.
traditional 10-minute deep research.
Cursor, and all major coding agents.
Context Benchmark Results
Measuring how effectively MCP servers provide context for implementing complex AI framework workflows
Deepcon leads with 90% accuracy
Tested across 20 real-world scenarios implementing Autogen, LangGraph, OpenAI Agents, Agno, and OpenRouter SDK. Each scenario evaluated by 3 LLMs (GPT-5, Grok-4, Deepseek-v3.2) for completeness and relevance. Deepcon provided sufficient context in 18/20 scenarios, outperforming all competitors by 25+ percentage points.
Average Token Usage per Task
Efficiency (Accuracy per 1K Tokens)
Token efficiency matters.
Deepcon achieves 90% success with only 2,365 avg tokens—less than half of Context7's 5,626 tokens at 65% success.
Trusted by engineers at
Example from our Database
OpenAI Docs Latest
GPT-5 API via client.responses.create() with model: "gpt-5". Supports input prompts, returns output_text. Import from "openai" package. Developer quickstart available on platform.openai.com...
Why Deepcon?
Built for agents that need comprehensive intelligence with zero token waste—enabling capabilities that were previously impossible.
Multi-Source Intelligence
Access tens of thousands of official documents, web search, deep research, and code search. Every tool your agent needs to find the right information.
Token-Optimized Delivery
Delivers exactly what's needed—nothing more, nothing less. Minimizes token waste while keeping your agent's context window optimized.
10x More Accurate
Delivers the most precise context for integrating latest features. When used with agents, error rates drop dramatically for production-ready results.
Always Up-to-Date
Real-time sync with latest docs, APIs, and releases. Your agents never work with stale information.