reshapr MCP Server
reshaprio/reshapr
[](https://agentrank-ai.com/tool/reshaprio--reshapr/?utm_source=badge&utm_medium=readme&utm_campaign=agentrank_badge) The open source, no-code MCP Server for AI-Native API Access
claude mcp add agentrank -- npx -y agentrank-mcp-server Overview
reshaprio/reshapr is a Java MCP server licensed under Apache-2.0. The open source, no-code MCP Server for AI-Native API Access Topics: agent-tools, ai-agents, ai-gateway, ai-infrastructure, ai-integration, ai-native, context-optimization, context-window, developer-tools, graphql-to-mcp, grpc, llm, mcp, openapi, rest-to-mcp, token-optimization, mcp-server, llm-agents, rest-api.
Ranked #674 out of 24846 indexed tools.
In the top 3% of all indexed tools.
Has 12 contributors.
Ecosystem
Score Breakdown
130 stars → growing community
Last commit 29d ago → recently updated
235/282 issues closed → responsive maintainer
12 contributors → active community
No dependents → no downstream usage
Weights: Freshness 20% · Issue Health 20% · Dependents 22% · Stars 10% · Contributors 8% · How we score →
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From the README
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# Welcome to reShapr 🚀
[**Website**](https://reshapr.io/) | [**About**](https://reshapr.io/about) | [**Docs**](https://reshapr.io/docs/) | [**Blog**](https://reshapr.io/blog) | [**Community**](https://reshapr.io/community)
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## ✨ What is reShapr?
**reShapr** is the open source, no-code MCP Server for AI-Native API Access. It bridges the gap between traditional REST/GraphQL/gRPC services and LLMs by transforming complex services into discoverable, optimized MCP tools.
<p align="center">
<a href="https://reshapr.io/docs/tutorials/getting-started">
</a>
<br/>
<em>✨ Transform any API into lean LLM contexts in seconds.</em>
</p>
> [!IMPORTANT]
> To get involved with our community, please familiarize yourself with the project's [Code of Conduct](./CODE_OF_CONDUCT.md).
### 🧠 Solving the "Context Window" Problem
One of the biggest hurdles in building AI agents is **Context Overload**. Sending massive JSON responses to an LLM wastes tokens and degrades performance.
Read full README on GitHub → Get the weekly AgentRank digest
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