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tura MCP Server

Tura-AI/tura

Score: 79.7 → 0% Rank #2035 MCP Server
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Build agent that uses 80% less token and delivers better results.

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Overview

Tura-AI/tura is a Rust tool licensed under AGPL-3.0. Build agent that uses 80% less token and delivers better results. Topics: agent, agentic-ai, coding-agent, context-engineering, developer-tools, developer-tools-ai-agent, harness-engineering, llm, terminal-based, token-optimization, token-usage, mcp.

Ranked #2035 out of 24846 indexed tools.

In the top 9% of all indexed tools.

Ecosystem

Rust AGPL-3.0
agentagentic-aicoding-agentcontext-engineeringdeveloper-toolsdeveloper-tools-ai-agentharness-engineeringllmterminal-basedtoken-optimizationtoken-usagemcp

Score Breakdown

StarsFreshnessIssue HealthContributorsDependents
Stars 15% 654

654 stars → growing community

Freshness 25% 1mo ago

Last commit 1mo ago → moderate activity

Issue Health 25% 64%

7/11 issues closed → decent issue management

Contributors 10% 6

6 contributors → small team

Dependents 25% 0

No dependents → no downstream usage

npm Downloads N/A
PyPI Downloads N/A
Forks 36
Description Good
License AGPL-3.0

Weights: Freshness 20% · Issue Health 20% · Dependents 22% · Stars 10% · Contributors 8% · How we score →

How to Improve

Description low impact

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Freshness high impact

Last commit was 35 days ago — a recent commit would boost your freshness score

Dependents medium impact

No downstream dependents detected yet — adoption by other projects is the strongest trust signal

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AgentRank score for Tura-AI/tura
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Matched Queries

topic:mcp

From the README

<p align="center">
  <a href="https://turaai.net/">
    
  </a>
</p>

<p align="center">
  <a href="https://turaai.net/"></a>
  <a href="https://turaai.net/benchmark"></a>
  <a href="https://www.npmjs.com/package/tura-ai"></a>
</p>

<p align="center"><strong>English</strong> | <a href="README.zh-CN.md">简体中文</a></p>

<h1 align="center">Tura: 16.7% better performance, 77.5% fewer tokens. </h1>

Tura is an open-source agent runtime harness that delivers better results with fewer tokens.

In a ReAct session, the model must re-enter after every tool result, repeatedly carrying the system prompt and a growing context. Tura turns the same task into one runtime-managed command graph, so deterministic execution continues without another model round trip.

<p align="center">
  
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<p align="center"><em>Tura executes in one turn the same workflow that a ReAct architecture needs five turns to complete.</em></p>

Across 20 DeepSWE v1.1 tasks, each run three times per agent, Tura creates a substa
Read full README on GitHub →

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