> For the complete documentation index, see [llms.txt](https://docs.algenta.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.algenta.ai/sdks.md). # SDKs - [Python SDK](https://docs.algenta.ai/sdks/python.md): Use Algenta from Python — install algenta-sdk, authenticate, and call the engine with a typed client. Includes runnable examples. - [Python client reference](https://docs.algenta.ai/sdks/python/overview.md): Install algenta-sdk, construct the sync or async AlgentaClient, configure retries and timeouts, handle typed errors, and jump to the Python method reference by domain. - [Simulations & queries](https://docs.algenta.ai/sdks/python/simulations-and-queries.md): Python SDK reference for the simulation and query methods — simulate, resolve, query, query\_batch, verify, recommend, score, compare, and plan\_decision. - [Decisions & products](https://docs.algenta.ai/sdks/python/decisions-and-products.md): Python SDK reference for decision memory and product intelligence — log\_decision, record\_outcome, execute\_decision, plus product\_decision, product\_optimize, and product\_forecast. - [Connectors & datasets](https://docs.algenta.ai/sdks/python/connectors-and-data.md): Python SDK reference for connectors and datasets — create, test, browse, and update connectors, then onboard, list, summarize, refresh, and delete datasets. - [Repository intelligence](https://docs.algenta.ai/sdks/python/repositories.md): Python SDK reference for repository intelligence — capabilities, snapshots, triage, decision plans, graph queries, simulate, and apply. - [LLM & embeddings](https://docs.algenta.ai/sdks/python/llm.md): Python SDK reference for the governed LLM surface — list\_models, tokenize, count\_tokens, chat\_completions, responses, embeddings, embedding\_similarity, and rerank. - [Agent runs](https://docs.algenta.ai/sdks/python/agent-runs.md): Python SDK reference for agent runs — launch, inspect, stream, pause/approve/resume, replay and fork agentic runs, with every AlgentaClient method and its endpoint. - [Jobs, triggers & capabilities](https://docs.algenta.ai/sdks/python/jobs-triggers-capabilities.md): Python SDK reference for async jobs, deployments, triggers, data sources, and the capability plane — every AlgentaClient method with its endpoint and return type. - [Account & control plane](https://docs.algenta.ai/sdks/python/account-and-control-plane.md): Python SDK reference for identity, usage, API keys, teams, billing, devices, audit logs, execution policy, and the platform contract — every AlgentaClient method and endpoint. - [TypeScript SDK](https://docs.algenta.ai/sdks/typescript.md): Use Algenta from TypeScript or JavaScript — install the SDK, authenticate, and call the engine with a typed client. Includes runnable examples. - [TypeScript client reference](https://docs.algenta.ai/sdks/typescript/overview.md): Install algenta-sdk, construct an AlgentaClient, and learn the promise-based method surface and the typed error hierarchy before you call the engine. - [Simulations & queries](https://docs.algenta.ai/sdks/typescript/simulations-and-queries.md): TypeScript SDK methods for Monte Carlo simulation, decision planning, recommendation, scoring, and the governed query family, each with its HTTP route. - [Decisions & products](https://docs.algenta.ai/sdks/typescript/decisions-and-products.md): TypeScript SDK methods for decision memory (log, list, outcome, execute, delete) and the high-level product endpoints for decision, optimize, retrieve, forecast, and agent runs. - [LLM & model discovery](https://docs.algenta.ai/sdks/typescript/llm.md): TypeScript SDK methods for the governed LLM surface — chat, responses, embeddings, rerank, tokenization, model artifacts — plus model catalog and runtime discovery. - [Connectors & data](https://docs.algenta.ai/sdks/typescript/connectors-and-data.md): TypeScript SDK methods for connectors, datasets, source registration, and repository intelligence — create, test, browse, onboard, snapshot, triage, and apply. - [Repository intelligence](https://docs.algenta.ai/sdks/typescript/repositories.md): TypeScript SDK reference for repository intelligence — snapshot a repo, triage an issue into ranked evidence, build a decision plan, query the symbol graph, simulate, and apply a fix. - [Agent runs](https://docs.algenta.ai/sdks/typescript/agent-runs.md): TypeScript SDK reference for agent runs — launch, stream, approve, fork, and replay runs, and query their events, checkpoints, mission events, and telemetry. - [Jobs, triggers & capabilities](https://docs.algenta.ai/sdks/typescript/jobs-triggers-capabilities.md): TypeScript SDK reference for async jobs, webhook triggers, and the capability plane — submit and poll jobs, register triggers, and route, execute, and bind capabilities. - [Account & control plane](https://docs.algenta.ai/sdks/typescript/account-and-control-plane.md): TypeScript SDK reference for the account and control plane — identity, usage, limits, billing, API keys, team, devices, audit logs, execution policy, deployments, health, and version. - [MCP server](https://docs.algenta.ai/sdks/mcp.md): Connect Algenta to MCP-compatible tools like Cursor and Claude Desktop. Configure the MCP server, authenticate, and verify the tools appear. - [Install from the MCP Registry](https://docs.algenta.ai/sdks/mcp-registry.md): Install the Algenta MCP server from the Official MCP Registry — io.github.thyn-ai/algenta — into Cursor, Claude Desktop, Claude Code, or Codex, passing your ALGENTA\_API\_KEY. - [Tool discovery](https://docs.algenta.ai/sdks/tool-discovery.md): How an AI agent or MCP client discovers Algenta's tools — list the gated tool catalog, read the machine-readable contract, and check the runtime manifest before planning. - [Testing with Algenta](https://docs.algenta.ai/sdks/testing.md): Test Algenta-backed code with the engine's determinism — assert stable decision\_hash values, replay recorded runs, mock the HTTP transport, and gate live tests on an API key. - [CLI reference](https://docs.algenta.ai/sdks/cli.md): Install and use the supported Algenta command-line surfaces without managing a separate compute runtime. --- # Agent Instructions This documentation is published with GitBook. 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