--- title: "langchain vs awesome-ai-agents-security" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/langchain-ai-langchain-vs-projectrecon-awesome-ai-agents-security" tools: ["langchain-ai-langchain", "projectrecon-awesome-ai-agents-security"] --- # langchain vs awesome-ai-agents-security *GraphCanon updated Jul 15, 2026* ## Verdict Pick langchain when license: langchain is MIT, awesome-ai-agents-security is Other; pick awesome-ai-agents-security when license: awesome-ai-agents-security is Other, langchain is MIT. [langchain](https://docs.langchain.com/langchain/) reports 142k GitHub stars, 24k forks, and 419 open issues, last pushed Jul 14, 2026. [awesome-ai-agents-security](https://github.com/ProjectRecon/awesome-ai-agents-security) has 54 stars, 62 forks, and 50 open issues, last pushed Jun 12, 2026. Figures are from public GitHub metadata via [langchain's repository](https://github.com/langchain-ai/langchain) and [awesome-ai-agents-security's repository](https://github.com/ProjectRecon/awesome-ai-agents-security). | | [langchain](/tools/langchain-ai-langchain.md) | [awesome-ai-agents-security](/tools/projectrecon-awesome-ai-agents-security.md) | | --- | --- | --- | | Tagline | The agent engineering platform. | A living map of the AI agent security ecosystem. | | Stars | 141,713 | 54 | | Forks | 23,545 | 62 | | Open issues | 419 | 50 | | Language | Python | - | | Adopt for | LangChain is an open-source platform designed specifically for building agents and applications that leverage large language models (LLMs). It provides a standard framework to develop interoperable components and connect | - | | Persona | - | - | | Runtime | - | - | | License | MIT License, allowing free use for both personal and commercial purposes under its stipulated terms. | Other | | Categories | AI Agents, LLM Frameworks | AI Agents, LLM Frameworks, Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [langchain](/tools/langchain-ai-langchain.md) | [awesome-ai-agents-security](/tools/projectrecon-awesome-ai-agents-security.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Steady (60%) | | Days since push | 0d | 32d | | Open issues (now) | 419 | 50 | | Full report | [trust report](/tools/langchain-ai-langchain/trust.md) | [trust report](/tools/projectrecon-awesome-ai-agents-security/trust.md) | ## Shared compatibility - **LangGraph**: [langchain](/tools/langchain-ai-langchain.md) - LangGraph integration; [awesome-ai-agents-security](/tools/projectrecon-awesome-ai-agents-security.md) - LangGraph integration ## Decision facts: langchain - **Pricing:** freemium - LangChain itself is open-source and free to use. However, it might rely on paid services or premium models from external platforms like OpenAI. - **Adopt for:** LangChain is an open-source platform designed specifically for building agents and applications that leverage large language models (LLMs). It provides a standard framework to develop interoperable components and connect - **License detail:** MIT License, allowing free use for both personal and commercial purposes under its stipulated terms. ## Choose when ### Choose langchain if… - License: langchain is MIT, awesome-ai-agents-security is Other. - Pricing: LangChain itself is open-source and free to use. However, it might rely on paid services or premium models from external platforms like OpenAI.. - Tags unique to langchain: agents, anthropic, chatgpt, deepagents. - * When aiming to build complex AI-powered agents or applications requiring high-level capabilities like planning, subagent interaction, and file system operations. ### Choose awesome-ai-agents-security if… - License: awesome-ai-agents-security is Other, langchain is MIT. - Tags unique to awesome-ai-agents-security: ai-security, autonomous-agents, awesome, awesome-list. - Also covers Vector Databases. ## When NOT to use langchain - * When working on smaller, less complex projects where full-scale integration with sophisticated components is not necessary as LangChain's extensive features might introduce unnecessary complexity. - * If you are primarily focused on JavaScript or TypeScript development as the primary focus of LangChain is Python. Although there is a JS/TS equivalent (LangChain.js), it may not offer the same depth - * For projects requiring heavy customization at lower levels, where a more granular control over individual components is required rather than working with an integrated framework. ## When NOT to use awesome-ai-agents-security - AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. - Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ## Common questions ### What is the difference between langchain and awesome-ai-agents-security? langchain: The agent engineering platform.. awesome-ai-agents-security: A living map of the AI agent security ecosystem.. See the comparison table for live GitHub stats and shared categories. ### When should I choose langchain over awesome-ai-agents-security? Choose langchain over awesome-ai-agents-security when License: langchain is MIT, awesome-ai-agents-security is Other; Pricing: LangChain itself is open-source and free to use. However, it might rely on paid services or premium models from external platforms like OpenAI.; Tags unique to langchain: agents, anthropic, chatgpt, deepagents; * When aiming to build complex AI-powered agents or applications requiring high-level capabilities like planning, subagent interaction, and file system operations. ### When should I choose awesome-ai-agents-security over langchain? Choose awesome-ai-agents-security over langchain when License: awesome-ai-agents-security is Other, langchain is MIT; Tags unique to awesome-ai-agents-security: ai-security, autonomous-agents, awesome, awesome-list; Also covers Vector Databases. ### When should I avoid langchain? * When working on smaller, less complex projects where full-scale integration with sophisticated components is not necessary as LangChain's extensive features might introduce unnecessary complexity. * If you are primarily focused on JavaScript or TypeScript development as the primary focus of LangChain is Python. Although there is a JS/TS equivalent (LangChain.js), it may not offer the same depth * For projects requiring heavy customization at lower levels, where a more granular control over individual components is required rather than working with an integrated framework. ### When should I avoid awesome-ai-agents-security? AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ### Is langchain or awesome-ai-agents-security more popular on GitHub? langchain has more GitHub stars (141,713 vs 54). Stars measure visibility, not whether either tool fits your constraints. ### Are langchain and awesome-ai-agents-security open source? Yes - both are open-source projects on GitHub (langchain: MIT, awesome-ai-agents-security: Other). ### Where can I find alternatives to langchain or awesome-ai-agents-security? GraphCanon lists graph-backed alternatives at [langchain alternatives](/tools/langchain-ai-langchain/alternatives) and [awesome-ai-agents-security alternatives](/tools/projectrecon-awesome-ai-agents-security/alternatives) ([langchain markdown twin](/tools/langchain-ai-langchain/alternatives.md), [awesome-ai-agents-security markdown twin](/tools/projectrecon-awesome-ai-agents-security/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/langchain-ai-langchain-vs-projectrecon-awesome-ai-agents-security.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, langchain or awesome-ai-agents-security? langchain: Very active. awesome-ai-agents-security: Steady. 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 langchain and awesome-ai-agents-security? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [langchain trust report](/tools/langchain-ai-langchain/trust); [awesome-ai-agents-security trust report](/tools/projectrecon-awesome-ai-agents-security/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=langchain-ai-langchain`](/api/graphcanon/graph?tool=langchain-ai-langchain) - 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/_