--- title: "Agent-Reach vs llm.ts" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/panniantong-agent-reach-vs-r2d4-llm-ts" tools: ["panniantong-agent-reach", "r2d4-llm-ts"] --- # Agent-Reach vs llm.ts *GraphCanon updated Jul 11, 2026* ## Verdict Pick Agent-Reach when agent-Reach is primarily Python; llm.ts is TypeScript; pick llm.ts when llm.ts is primarily TypeScript; Agent-Reach is Python. [Agent-Reach](https://github.com/Panniantong/Agent-Reach) reports 55k GitHub stars, 4.5k forks, and 144 open issues, last pushed Jul 10, 2026. [llm.ts](https://github.com/r2d4/llm.ts) has 213 stars, 9 forks, and 2 open issues, last pushed May 9, 2023. Figures are from public GitHub metadata via [Agent-Reach's repository](https://github.com/Panniantong/Agent-Reach) and [llm.ts's repository](https://github.com/r2d4/llm.ts). | | [Agent-Reach](/tools/panniantong-agent-reach.md) | [llm.ts](/tools/r2d4-llm-ts.md) | | --- | --- | --- | | Tagline | Give your AI agent eyes to see the entire internet. Read & search Twitter, Reddit, YouTube, GitHub, Bilibili, XiaoHongShu — one CLI, zero API fees. | Call any LLM with a single API. Zero dependencies. | | Stars | 54,715 | 213 | | Forks | 4,509 | 9 | | Open issues | 144 | 2 | | Language | Python | TypeScript | | Adopt for | - | - | | Persona | - | - | | Runtime | - | - | | License | MIT | MIT | | Categories | LLM Frameworks, AI Agents, Developer Tools | LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [Agent-Reach](/tools/panniantong-agent-reach.md) | [llm.ts](/tools/r2d4-llm-ts.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Dormant (18%) | | Days since push | 0d | 1158d | | Open issues (now) | 144 | 2 | | Security scan | No MCP manifest | No lockfile | | Full report | [trust report](/tools/panniantong-agent-reach/trust.md) | [trust report](/tools/r2d4-llm-ts/trust.md) | ## Choose when ### Choose Agent-Reach if… - Agent-Reach is primarily Python; llm.ts is TypeScript. - Tags unique to Agent-Reach: agent-infrastructure, ai-search, bilibili, claude-code. - Also covers AI Agents, Developer Tools. ### Choose llm.ts if… - llm.ts is primarily TypeScript; Agent-Reach is Python. - Tags unique to llm.ts: llms, llm, ai, openai. - Leaner open-issue backlog (2). ## When NOT to use Agent-Reach - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. - AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. - Developer Tools: A gateway is overkill when you're pinned to a single provider and model. ## When NOT to use llm.ts - Last GitHub push was 1159 days ago (dormant maintenance, May 9, 2023). Validate activity before betting a new project on llm.ts. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ## Common questions ### What is the difference between Agent-Reach and llm.ts? Agent-Reach: Give your AI agent eyes to see the entire internet. Read & search Twitter, Reddit, YouTube, GitHub, Bilibili, XiaoHongShu — one CLI, zero API fees.. llm.ts: Call any LLM with a single API. Zero dependencies.. See the comparison table for live GitHub stats and shared categories. ### When should I choose Agent-Reach over llm.ts? Choose Agent-Reach over llm.ts when Agent-Reach is primarily Python; llm.ts is TypeScript; Tags unique to Agent-Reach: agent-infrastructure, ai-search, bilibili, claude-code; Also covers AI Agents, Developer Tools. ### When should I choose llm.ts over Agent-Reach? Choose llm.ts over Agent-Reach when llm.ts is primarily TypeScript; Agent-Reach is Python; Tags unique to llm.ts: llms, llm, ai, openai; Leaner open-issue backlog (2). ### When should I avoid Agent-Reach? LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. Developer Tools: A gateway is overkill when you're pinned to a single provider and model. ### When should I avoid llm.ts? Last GitHub push was 1159 days ago (dormant maintenance, May 9, 2023). Validate activity before betting a new project on llm.ts. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ### Is Agent-Reach or llm.ts more popular on GitHub? Agent-Reach has more GitHub stars (54,715 vs 213). Stars measure visibility, not whether either tool fits your constraints. ### Are Agent-Reach and llm.ts open source? Yes - both are open-source projects on GitHub (Agent-Reach: MIT, llm.ts: MIT). ### Where can I find alternatives to Agent-Reach or llm.ts? GraphCanon lists graph-backed alternatives at [Agent-Reach alternatives](/tools/panniantong-agent-reach/alternatives) and [llm.ts alternatives](/tools/r2d4-llm-ts/alternatives) ([Agent-Reach markdown twin](/tools/panniantong-agent-reach/alternatives.md), [llm.ts markdown twin](/tools/r2d4-llm-ts/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/panniantong-agent-reach-vs-r2d4-llm-ts.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, Agent-Reach or llm.ts? Agent-Reach: Very active. llm.ts: 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 Agent-Reach and llm.ts? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [Agent-Reach trust report](/tools/panniantong-agent-reach/trust); [llm.ts trust report](/tools/r2d4-llm-ts/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=panniantong-agent-reach`](/api/graphcanon/graph?tool=panniantong-agent-reach) - 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/_