--- title: "athina-evals vs context7" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/athina-ai-athina-evals-vs-upstash-context7" tools: ["athina-ai-athina-evals", "upstash-context7"] --- # athina-evals vs context7 *GraphCanon updated Jul 11, 2026* ## Verdict Pick athina-evals when athina-evals is primarily Python; context7 is TypeScript; pick context7 when context7 is primarily TypeScript; athina-evals is Python. [athina-evals](https://docs.athina.ai) reports 301 GitHub stars, 22 forks, and 3 open issues, last pushed Jun 6, 2025. [context7](https://context7.com) has 59k stars, 2.8k forks, and 28 open issues, last pushed Jul 10, 2026. Figures are from public GitHub metadata via [athina-evals's repository](https://github.com/athina-ai/athina-evals) and [context7's repository](https://github.com/upstash/context7). | | [athina-evals](/tools/athina-ai-athina-evals.md) | [context7](/tools/upstash-context7.md) | | --- | --- | --- | | Tagline | Python SDK for running evaluations on LLM generated responses | Up-to-date code documentation for LLMs and AI code editors | | Stars | 301 | 58,913 | | Forks | 22 | 2,762 | | Open issues | 3 | 28 | | Language | Python | TypeScript | | Adopt for | - | Context7 is a platform devoted to providing updated code documentation specifically tailored for LLMs (Large Language Models) and AI-based code editing tools. It uses TypeScript and operates under the MIT license. | | Persona | - | - | | Runtime | - | - | | License | - | MIT | | Categories | Developer Tools, Evaluation & Observability, LLM Frameworks | Developer Tools, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [athina-evals](/tools/athina-ai-athina-evals.md) | [context7](/tools/upstash-context7.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Very active (96%) | | Days since push | 399d | 0d | | Open issues (now) | 3 | 28 | | Security scan | No lockfile | No MCP manifest | | Full report | [trust report](/tools/athina-ai-athina-evals/trust.md) | [trust report](/tools/upstash-context7/trust.md) | ## Decision facts: context7 - **Adopt for:** Context7 is a platform devoted to providing updated code documentation specifically tailored for LLMs (Large Language Models) and AI-based code editing tools. It uses TypeScript and operates under the MIT license. ## Choose when ### Choose athina-evals if… - athina-evals is primarily Python; context7 is TypeScript. - Tags unique to athina-evals: evaluation, evaluation-framework, evaluation-metrics, llm-eval. - Also covers Evaluation & Observability. ### Choose context7 if… - context7 is primarily TypeScript; athina-evals is Python. - Tags unique to context7: llm, mcp, mcp-server, vibe-coding. - When your project heavily relies on Large Language Models or AI-based code editors for enhancing development efficiency. ## When NOT to use athina-evals - Last GitHub push was 400 days ago (dormant maintenance, Jun 6, 2025). Validate activity before betting a new project on athina-evals. - Developer Tools: A gateway is overkill when you're pinned to a single provider and model. - Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ## When NOT to use context7 - Avoid Context7 if your current project doesn't involve integration with Large Language Models or any AI-driven code editing utilities, as it will not offer significant advantages. - If your team strictly adheres to a development workflow that does not benefit from having real-time documentation tailored for LLMs and AI code editors, opting for more general developer tools may be更 ## Common questions ### What is the difference between athina-evals and context7? athina-evals: Python SDK for running evaluations on LLM generated responses. context7: Up-to-date code documentation for LLMs and AI code editors. See the comparison table for live GitHub stats and shared categories. ### When should I choose athina-evals over context7? Choose athina-evals over context7 when athina-evals is primarily Python; context7 is TypeScript; Tags unique to athina-evals: evaluation, evaluation-framework, evaluation-metrics, llm-eval; Also covers Evaluation & Observability. ### When should I choose context7 over athina-evals? Choose context7 over athina-evals when context7 is primarily TypeScript; athina-evals is Python; Tags unique to context7: llm, mcp, mcp-server, vibe-coding; When your project heavily relies on Large Language Models or AI-based code editors for enhancing development efficiency. ### When should I avoid athina-evals? Last GitHub push was 400 days ago (dormant maintenance, Jun 6, 2025). Validate activity before betting a new project on athina-evals. Developer Tools: A gateway is overkill when you're pinned to a single provider and model. Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ### When should I avoid context7? Avoid Context7 if your current project doesn't involve integration with Large Language Models or any AI-driven code editing utilities, as it will not offer significant advantages. If your team strictly adheres to a development workflow that does not benefit from having real-time documentation tailored for LLMs and AI code editors, opting for more general developer tools may be更 ### Is athina-evals or context7 more popular on GitHub? context7 has more GitHub stars (58,913 vs 301). Stars measure visibility, not whether either tool fits your constraints. ### Are athina-evals and context7 open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to athina-evals or context7? GraphCanon lists graph-backed alternatives at [athina-evals alternatives](/tools/athina-ai-athina-evals/alternatives) and [context7 alternatives](/tools/upstash-context7/alternatives) ([athina-evals markdown twin](/tools/athina-ai-athina-evals/alternatives.md), [context7 markdown twin](/tools/upstash-context7/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/athina-ai-athina-evals-vs-upstash-context7.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, athina-evals or context7? athina-evals: Dormant. context7: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for athina-evals and context7? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [athina-evals trust report](/tools/athina-ai-athina-evals/trust); [context7 trust report](/tools/upstash-context7/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=athina-ai-athina-evals`](/api/graphcanon/graph?tool=athina-ai-athina-evals) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_