--- title: "contexto vs graphify" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/ekailabs-contexto-vs-graphify-labs-graphify" tools: ["ekailabs-contexto", "graphify-labs-graphify"] --- # contexto vs graphify *GraphCanon updated Jul 11, 2026* ## Verdict Pick contexto when contexto is primarily TypeScript; graphify is Python; pick graphify when graphify is primarily Python; contexto is TypeScript. [contexto](https://www.getcontexto.com) reports 629 GitHub stars, 23 forks, and 21 open issues, last pushed Jun 10, 2026. [graphify](https://graphifylabs.ai/) has 82k stars, 8.1k forks, and 452 open issues, last pushed Jul 11, 2026. Figures are from public GitHub metadata via [contexto's repository](https://github.com/ekailabs/contexto) and [graphify's repository](https://github.com/Graphify-Labs/graphify). | | [contexto](/tools/ekailabs-contexto.md) | [graphify](/tools/graphify-labs-graphify.md) | | --- | --- | --- | | Tagline | Context Engine for your long-running AI agents | Turn any code or documentation into a queryable knowledge graph | | Stars | 629 | 82,139 | | Forks | 23 | 8,086 | | Open issues | 21 | 452 | | Language | TypeScript | Python | | Adopt for | - | Graphify transforms a variety of inputs into a unified knowledge graph, ideal for creating searchable insights from mixed content types. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | MIT | | Categories | AI Agents, Data & Retrieval, Evaluation & Observability | Data & Retrieval, AI Agents | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [contexto](/tools/ekailabs-contexto.md) | [graphify](/tools/graphify-labs-graphify.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Very active (96%) | | Days since push | 31d | 0d | | Open issues (now) | 21 | 452 | | Full report | [trust report](/tools/ekailabs-contexto/trust.md) | [trust report](/tools/graphify-labs-graphify/trust.md) | ## Decision facts: graphify - **Requirements:** Ensure to install from the correct PyPI package named `graphifyy` (with double 'y') and not other similar-named packages which are unaffiliated.; Installation involves setting up a Python environment ('venv') and ensuring all required extras are installed. - **Adopt for:** Graphify transforms a variety of inputs into a unified knowledge graph, ideal for creating searchable insights from mixed content types. ## Choose when ### Choose contexto if… - contexto is primarily TypeScript; graphify is Python. - License: contexto is Apache-2.0, graphify is MIT. - Tags unique to contexto: typescript. - Also covers Evaluation & Observability. - contexto ships Docker support for self-hosted deployment. ### Choose graphify if… - graphify is primarily Python; contexto is TypeScript. - License: graphify is MIT, contexto is Apache-2.0. - Requirements: Ensure to install from the correct PyPI package named `graphifyy` (with double 'y') and not other similar-named packages which are unaffiliated.; Installation involves setting up a Python environment ('venv') and ensuring all required extras are installed.. - Tags unique to graphify: gemini, rag, codex, skills. - When you need to turn diverse file types (code, SQL schemas, documents, images) into a single queryable data structure that can be searched and analyzed together. ## When NOT to use contexto - AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. - Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough. - Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. ## When NOT to use graphify - If the project exclusively involves text-based content without requiring integration or querying across different file types (e.g., plain documents with no need for cross-referencing). - Avoid using Graphify if you are looking for a tool that focuses solely on visual graph representation without the depth of semantic querying capabilities. ## Common questions ### What is the difference between contexto and graphify? contexto: Context Engine for your long-running AI agents. graphify: Turn any code or documentation into a queryable knowledge graph. See the comparison table for live GitHub stats and shared categories. ### When should I choose contexto over graphify? Choose contexto over graphify when contexto is primarily TypeScript; graphify is Python; License: contexto is Apache-2.0, graphify is MIT; Tags unique to contexto: typescript; Also covers Evaluation & Observability; contexto ships Docker support for self-hosted deployment. ### When should I choose graphify over contexto? Choose graphify over contexto when graphify is primarily Python; contexto is TypeScript; License: graphify is MIT, contexto is Apache-2.0; Requirements: Ensure to install from the correct PyPI package named `graphifyy` (with double 'y') and not other similar-named packages which are unaffiliated.; Installation involves setting up a Python environment ('venv') and ensuring all required extras are installed.; Tags unique to graphify: gemini, rag, codex, skills; When you need to turn diverse file types (code, SQL schemas, documents, images) into a single queryable data structure that can be searched and analyzed together. ### When should I avoid contexto? AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough. Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. ### When should I avoid graphify? If the project exclusively involves text-based content without requiring integration or querying across different file types (e.g., plain documents with no need for cross-referencing). Avoid using Graphify if you are looking for a tool that focuses solely on visual graph representation without the depth of semantic querying capabilities. ### Is contexto or graphify more popular on GitHub? graphify has more GitHub stars (82,139 vs 629). Stars measure visibility, not whether either tool fits your constraints. ### Are contexto and graphify open source? Yes - both are open-source projects on GitHub (contexto: Apache-2.0, graphify: MIT). ### Where can I find alternatives to contexto or graphify? GraphCanon lists graph-backed alternatives at [contexto alternatives](/tools/ekailabs-contexto/alternatives) and [graphify alternatives](/tools/graphify-labs-graphify/alternatives) ([contexto markdown twin](/tools/ekailabs-contexto/alternatives.md), [graphify markdown twin](/tools/graphify-labs-graphify/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/ekailabs-contexto-vs-graphify-labs-graphify.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, contexto or graphify? contexto: Steady. graphify: 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 contexto and graphify? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [contexto trust report](/tools/ekailabs-contexto/trust); [graphify trust report](/tools/graphify-labs-graphify/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=ekailabs-contexto`](/api/graphcanon/graph?tool=ekailabs-contexto) - 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/_