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Vardan Botta"},"license":"MIT","homepage":"https://github.com/abhishekvardanbotta/kiln#readme","keywords":["kiln","cli","ai","agent","agents","framework","runtime","workflow","orchestration","llm","openai","claude","gemini","groq"],"repository":{"type":"git","url":"git+https://github.com/abhishekvardanbotta/kiln.git"},"description":"A CLI + SDK for building and orchestrating AI agents - real provider calls, tool-calling, structured output, teams, MCP debugging, and a DAG orchestrator.","maintainers":[{"name":"abhishekvardanbotta","email":"abhiuma2005@gmail.com"}],"readme":"# kiln\r\n\r\nA CLI + SDK for building and orchestrating AI agents. Real provider calls (OpenAI, Groq, Ollama), an\r\nautomatic tool-calling loop, self-correcting structured output, MCP support, and a DAG orchestrator with\r\nconcurrency pooling and cascading failure isolation — so you write agent logic, not infrastructure.\r\n\r\n**→ [KILN.md](./KILN.md) is the full reference** — written so an AI assistant can read it once and use\r\nkiln correctly. Point Claude/Cursor/whatever you use at that file; this README is just the map.\r\n\r\n## Install\r\n\r\n```sh\r\nnpm install @abhishekvardanbotta/kiln     # as a dependency, imported via createKiln()\r\nnpm install -g @abhishekvardanbotta/kiln  # as a CLI, exposes the `kiln` command\r\n```\r\n\r\n## 60-second tour\r\n\r\n```sh\r\nkiln init my-agents && cd my-agents   # one project holds unlimited agents\r\nkiln agent add forecaster              # scaffolds src/agents/forecaster.ts\r\nkiln validate && kiln pack && kiln install my-agents-0.1.0.agent\r\nkiln run my-agents:forecaster --query \"Tokyo\"\r\nkiln logs <runId>                      # replay exactly what happened\r\nkiln serve --port 4500                 # REST + SSE over HTTP for any backend language\r\n```\r\n\r\nOr skip the CLI entirely and embed it in a Node/TypeScript backend:\r\n\r\n```ts\r\nimport { createKiln } from \"@abhishekvardanbotta/kiln\";\r\n\r\nconst kiln = createKiln();\r\nawait kiln.orchestrate([\r\n  { id: \"forecaster\", agent: { directory: \"./my-agents\", agentName: \"forecaster\" }, input: { city: \"Paris\" } },\r\n  { id: \"advisor\", dependsOn: [\"forecaster\"], agent: { directory: \"./my-agents\", agentName: \"advisor\" },\r\n    input: (ctx) => ({ forecast: ctx.outputs.forecaster }) },\r\n]);\r\n```\r\n\r\nSee **[KILN.md](./KILN.md)** for `defineAgent`/`defineTool`/`connectMCP`, the `ctx.ai` API\r\n(`chat`/`stream`/`json`/`run`/`object`), the orchestrator, the HTTP server's endpoints, provider setup,\r\nand common mistakes to avoid.\r\n\r\n## Status\r\n\r\nProviders: `openai`, `groq` and `gemini` go through a shared OpenAI-compatible adapter, `ollama` runs\r\nlocally through the same one, and `claude` has its own adapter for Anthropic's non-OpenAI message shape.\r\nAll five are real. Kiln's own package registry commands (`search`/`publish`/`login`) are still mocked —\r\nno real network calls.\r\n\r\n## License\r\n\r\nMIT\r\n","readmeFilename":"README.md"}