--- title: "llm_agents vs agency" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/mpaepper-llm-agents-vs-neurocult-agency" tools: ["mpaepper-llm-agents", "neurocult-agency"] --- # llm_agents vs agency *GraphCanon updated Aug 21, 2026* ## Verdict Pick llm_agents if llm_agents is a Python library enabling users to build simple agents directed by large language models, featuring functions like executing Python code and using Google search; pick agency if agency is a Go-idiomatic library aimed at developers looking to work with Large Language Models and generative AI techniques. [llm_agents](https://www.paepper.com/blog/posts/intelligent-agents-guided-by-llms/) reports 1.1k GitHub stars, 85 forks, and 3 open issues, last pushed Jun 23, 2025. [agency](https://github.com/neurocult/agency) has 514 stars, 36 forks, and 4 open issues, last pushed Jan 8, 2025. Figures are from public GitHub metadata via [llm_agents's repository](https://github.com/mpaepper/llm_agents) and [agency's repository](https://github.com/neurocult/agency). | | [llm_agents](/tools/mpaepper-llm-agents.md) | [agency](/tools/neurocult-agency.md) | | --- | --- | --- | | Tagline | Library to build agents controlled by LLMs | Library for exploring Large Language Models and generative AI in Go | | Stars | 1,053 | 514 | | Forks | 85 | 36 | | Open issues | 3 | 4 | | Language | Python | Go | | Adopt for | llm_agents is a Python library enabling users to build simple agents directed by large language models, featuring functions like executing Python code and using Google search. | Agency is a Go-idiomatic library aimed at developers looking to work with Large Language Models and generative AI techniques. | | Persona | - | - | | Runtime | - | - | | License | MIT | MIT | | Categories | AI Agents | AI Agents, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [llm_agents](/tools/mpaepper-llm-agents.md) | [agency](/tools/neurocult-agency.md) | | --- | --- | --- | | Days since push | 418d | 589d | | Open issues (now) | 3 | 4 | | Stars delta | +3 (30d) | +2 (30d) | | Owner type | User | Organization | | Full report | [trust report](/tools/mpaepper-llm-agents/trust.md) | [trust report](/tools/neurocult-agency/trust.md) | ## Decision facts: llm_agents - **Requirements:** Min 1 GB RAM; Requires the installation of requirements specified by running `pip install -r requirements.txt` followed by `pip install -e .`.; Dependencies include setting up environment variables for `OPENAI_API_KEY` to use OpenAI API and optionally `SERPAPI_API_KEY` if Google search tool is utilized. - **Adopt for:** llm_agents is a Python library enabling users to build simple agents directed by large language models, featuring functions like executing Python code and using Google search. ## Decision facts: agency - **Pricing:** freemium - Agency is available under MIT license and is free for use, modification, and distribution. Additional services or integrations might involve costs not outlined within the repository. - **Adopt for:** Agency is a Go-idiomatic library aimed at developers looking to work with Large Language Models and generative AI techniques. ## Choose when ### Choose llm_agents if… - llm_agents is primarily Python; agency is Go. - Requirements: Min 1 GB RAM; Requires the installation of requirements specified by running `pip install -r requirements.txt` followed by `pip install -e .`.; Dependencies include setting up environment variables for `OPENAI_API_KEY` to use OpenAI API and optionally `SERPAPI_API_KEY` if Google search tool is utilized.. - Tags unique to llm_agents: deep-learning, langchain, llms, machine-learning. - Use llm_agents when you require a lightweight solution for building agents controlled by LLMs with specific tools such as Python REPL execution or Hacker News search. ### Choose agency if… - agency is primarily Go; llm_agents is Python. - Pricing: Agency is available under MIT license and is free for use, modification, and distribution. Additional services or integrations might involve costs not outlined within the repository.. - Tags unique to agency: agents, generative-ai, go, language-models. - Also covers LLM Frameworks. - If you're proficient in Go and want to implement LLMs within a familiar ecosystem, consider agency. ## When NOT to use llm_agents - Avoid llm_agents if you need a more robust and feature-rich product for complex tasks that require extensive integration capabilities beyond Python REPL, Google search, and Hacker News. - Do not choose it when you are looking for advanced abstraction layers like those found in LangChain, as llm_agents aims to remain simple with fewer files and a straightforward core. ## When NOT to use agency - Avoid agency if your primary programming expertise lies outside of the Go ecosystem. - Not recommended if you require real-time performance characteristics that surpass what typical LLM exploration libraries can provide. ## Common questions ### What is the difference between llm_agents and agency? llm_agents: Library to build agents controlled by LLMs. agency: Library for exploring Large Language Models and generative AI in Go. See the comparison table for live GitHub stats and shared categories. ### When should I choose llm_agents over agency? Choose llm_agents over agency when llm_agents is primarily Python; agency is Go; Requirements: Min 1 GB RAM; Requires the installation of requirements specified by running `pip install -r requirements.txt` followed by `pip install -e .`.; Dependencies include setting up environment variables for `OPENAI_API_KEY` to use OpenAI API and optionally `SERPAPI_API_KEY` if Google search tool is utilized.; Tags unique to llm_agents: deep-learning, langchain, llms, machine-learning; Use llm_agents when you require a lightweight solution for building agents controlled by LLMs with specific tools such as Python REPL execution or Hacker News search. ### When should I choose agency over llm_agents? Choose agency over llm_agents when agency is primarily Go; llm_agents is Python; Pricing: Agency is available under MIT license and is free for use, modification, and distribution. Additional services or integrations might involve costs not outlined within the repository.; Tags unique to agency: agents, generative-ai, go, language-models; Also covers LLM Frameworks; If you're proficient in Go and want to implement LLMs within a familiar ecosystem, consider agency. ### When should I avoid llm_agents? Avoid llm_agents if you need a more robust and feature-rich product for complex tasks that require extensive integration capabilities beyond Python REPL, Google search, and Hacker News. Do not choose it when you are looking for advanced abstraction layers like those found in LangChain, as llm_agents aims to remain simple with fewer files and a straightforward core. ### When should I avoid agency? Avoid agency if your primary programming expertise lies outside of the Go ecosystem. Not recommended if you require real-time performance characteristics that surpass what typical LLM exploration libraries can provide. ### Is llm_agents or agency more popular on GitHub? llm_agents has more GitHub stars (1,053 vs 514). Stars measure visibility, not whether either tool fits your constraints. ### Are llm_agents and agency open source? Yes - both are open-source projects on GitHub (llm_agents: MIT, agency: MIT). ### Where can I find alternatives to llm_agents or agency? GraphCanon lists graph-backed alternatives at [llm_agents alternatives](/tools/mpaepper-llm-agents/alternatives) and [agency alternatives](/tools/neurocult-agency/alternatives) ([llm_agents markdown twin](/tools/mpaepper-llm-agents/alternatives.md), [agency markdown twin](/tools/neurocult-agency/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/mpaepper-llm-agents-vs-neurocult-agency.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, llm_agents or agency? llm_agents: Dormant. agency: Dormant. 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 llm_agents and agency? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [llm_agents trust report](/tools/mpaepper-llm-agents/trust); [agency trust report](/tools/neurocult-agency/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=mpaepper-llm-agents`](/api/graphcanon/graph?tool=mpaepper-llm-agents) - 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/_