--- title: "core vs anything-llm" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/cheshire-cat-ai-core-vs-mintplex-labs-anything-llm" tools: ["cheshire-cat-ai-core", "mintplex-labs-anything-llm"] --- # core vs anything-llm *GraphCanon updated Jul 11, 2026* ## Verdict Pick core when core is primarily Python; anything-llm is JavaScript; pick anything-llm when anything-llm is primarily JavaScript; core is Python. [core](https://cheshirecat.ai) reports 3.1k GitHub stars, 410 forks, and 4 open issues, last pushed Jul 8, 2026. [anything-llm](https://anythingllm.com) has 63k stars, 6.9k forks, and 320 open issues, last pushed Jul 11, 2026. Figures are from public GitHub metadata via [core's repository](https://github.com/cheshire-cat-ai/core) and [anything-llm's repository](https://github.com/Mintplex-Labs/anything-llm). | | [core](/tools/cheshire-cat-ai-core.md) | [anything-llm](/tools/mintplex-labs-anything-llm.md) | | --- | --- | --- | | Tagline | AI agent microservice | Self-hosted agent experience with deployment scripts for multiple environments | | Stars | 3,072 | 63,100 | | Forks | 410 | 6,907 | | Open issues | 4 | 320 | | Language | Python | JavaScript | | Adopt for | - | Self-hosted AI agent experience with robust deployment scripts across multiple environments. | | Persona | - | - | | Runtime | - | - | | License | GPL-3.0 | MIT | | Categories | AI Agents, LLM Frameworks, Vector Databases | AI Agents, Inference & Serving | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [core](/tools/cheshire-cat-ai-core.md) | [anything-llm](/tools/mintplex-labs-anything-llm.md) | | --- | --- | --- | | Days since push | 2d | 0d | | Open issues (now) | 4 | 320 | | Security scan | 2 low (2 low) | No lockfile | | Full report | [trust report](/tools/cheshire-cat-ai-core/trust.md) | [trust report](/tools/mintplex-labs-anything-llm/trust.md) | ## Decision facts: anything-llm - **Adopt for:** Self-hosted AI agent experience with robust deployment scripts across multiple environments. ## Choose when ### Choose core if… - core is primarily Python; anything-llm is JavaScript. - License: core is GPL-3.0, anything-llm is MIT. - Tags unique to core: ag-ui-protocol, agent, ai, assistant. - Also covers LLM Frameworks, Vector Databases. ### Choose anything-llm if… - anything-llm is primarily JavaScript; core is Python. - License: anything-llm is MIT, core is GPL-3.0. - Tags unique to anything-llm: agent-computer, agent-harness, agentic-ai, llm. - Also covers Inference & Serving. - When you need flexibility in deploying your AI agents on various cloud platforms like AWS, GCP, Digital Ocean, and more. ## When NOT to use core - 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. ## When NOT to use anything-llm - Avoid if you require an agent without additional setup or prefer SaaS solutions over self-managed deployments. - Not suitable for users who are looking for no-code alternatives as setting up AnythingLLM might necessitate some coding knowledge despite offering multiple scripts and methods. ## Common questions ### What is the difference between core and anything-llm? core: AI agent microservice. anything-llm: Self-hosted agent experience with deployment scripts for multiple environments. See the comparison table for live GitHub stats and shared categories. ### When should I choose core over anything-llm? Choose core over anything-llm when core is primarily Python; anything-llm is JavaScript; License: core is GPL-3.0, anything-llm is MIT; Tags unique to core: ag-ui-protocol, agent, ai, assistant; Also covers LLM Frameworks, Vector Databases. ### When should I choose anything-llm over core? Choose anything-llm over core when anything-llm is primarily JavaScript; core is Python; License: anything-llm is MIT, core is GPL-3.0; Tags unique to anything-llm: agent-computer, agent-harness, agentic-ai, llm; Also covers Inference & Serving; When you need flexibility in deploying your AI agents on various cloud platforms like AWS, GCP, Digital Ocean, and more. ### When should I avoid core? 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. ### When should I avoid anything-llm? Avoid if you require an agent without additional setup or prefer SaaS solutions over self-managed deployments. Not suitable for users who are looking for no-code alternatives as setting up AnythingLLM might necessitate some coding knowledge despite offering multiple scripts and methods. ### Is core or anything-llm more popular on GitHub? anything-llm has more GitHub stars (63,100 vs 3,072). Stars measure visibility, not whether either tool fits your constraints. ### Are core and anything-llm open source? Yes - both are open-source projects on GitHub (core: GPL-3.0, anything-llm: MIT). ### Where can I find alternatives to core or anything-llm? GraphCanon lists graph-backed alternatives at [core alternatives](/tools/cheshire-cat-ai-core/alternatives) and [anything-llm alternatives](/tools/mintplex-labs-anything-llm/alternatives) ([core markdown twin](/tools/cheshire-cat-ai-core/alternatives.md), [anything-llm markdown twin](/tools/mintplex-labs-anything-llm/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/cheshire-cat-ai-core-vs-mintplex-labs-anything-llm.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, core or anything-llm? core: Very active. anything-llm: 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 core and anything-llm? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [core trust report](/tools/cheshire-cat-ai-core/trust); [anything-llm trust report](/tools/mintplex-labs-anything-llm/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=cheshire-cat-ai-core`](/api/graphcanon/graph?tool=cheshire-cat-ai-core) - 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/_