# Frameworkr — AI Agent Tools Catalog

> Curated AI agent infrastructure — editorially reviewed and mapped to layers of an AI agent architecture. Start with the [agent architecture guide](https://www.frameworkr.ai/blog/what-is-an-ai-agent-architecture.md) before shopping by category.

Markdown versions of each tool are available at `<tool-url>.md`.

## Orchestration (architecture layer)

Frameworks that coordinate agent logic, tool use, and decision flow

- [Graphify](https://www.frameworkr.ai/tools/graphify.md): Turn any codebase into a queryable knowledge graph.
- [LangChain](https://www.frameworkr.ai/tools/langchain.md): The most widely-adopted framework for building LLM-powered applications and agents
- [LlamaIndex](https://www.frameworkr.ai/tools/llamaindex.md): The data framework for building LLM applications over custom knowledge sources
- [Open Multi-Agent](https://www.frameworkr.ai/tools/open-multi-agent.md): TypeScript AI agent orchestration framework with dynamic workflows.

## Models (architecture layer)

LLM providers and local inference options

- [Anthropic Claude API](https://www.frameworkr.ai/tools/anthropic-claude.md): State-of-the-art frontier models built for safe, steerable, and capable agentic use
- [Groq](https://www.frameworkr.ai/tools/groq.md): Fastest inference API for open-source models — purpose-built for speed
- [Ollama](https://www.frameworkr.ai/tools/ollama.md): Run open-source LLMs locally with a simple API and no cloud dependency
- [OpenAI API](https://www.frameworkr.ai/tools/openai.md): The GPT model family with vision, audio, and the broadest tool-calling ecosystem

## Memory & Vector (architecture layer)

Storage layers for agent context, embeddings, and retrieval

- [Chroma](https://www.frameworkr.ai/tools/chroma.md): Open-source embedding database — the fast path from prototype to local vector search
- [Pinecone](https://www.frameworkr.ai/tools/pinecone.md): Managed vector database built for production-scale semantic search and agent memory

## Actions & Integrations (architecture layer)

Tools that give agents the ability to act on external systems

- [Composio](https://www.frameworkr.ai/tools/composio.md): 250+ pre-built tool integrations so agents can act on external systems out of the box
- [Zapier](https://www.frameworkr.ai/tools/zapier.md): No-code automation backbone connecting 7,000+ apps for agent-triggered workflows

## Browser & Scraping (architecture layer)

Headless browser control and web data extraction

- [Atomic Agent](https://www.frameworkr.ai/tools/atomic-agent.md): A local-first AI agent that runs on your machine, with local or cloud models.
- [Browser Use](https://www.frameworkr.ai/tools/browser-use.md): Make websites accessible for AI agents. Automate tasks online with ease.
- [Browserbase](https://www.frameworkr.ai/tools/browserbase.md): Headless browser infrastructure for agents — reliable, scalable, cloud-native
- [CloakBrowser](https://www.frameworkr.ai/tools/cloakbrowser.md): Stealth Chromium that passes every bot detection test.
- [Obscura](https://www.frameworkr.ai/tools/obscura.md): The open-source headless browser for AI agents and web scraping.
- [OpenCLI](https://www.frameworkr.ai/tools/opencli.md): Convert any website into a CLI & run Browser Use on your logged-in Chrome.

## Triggers & Scheduling (architecture layer)

Event-driven and scheduled agent execution

- [Trigger.dev](https://www.frameworkr.ai/tools/triggerdev.md): Code-native background jobs and event-driven agent execution with full observability

## Hosting & Infra (architecture layer)

Where agents run — serverless, containerised, or edge

- [Railway](https://www.frameworkr.ai/tools/railway.md): Deploy any containerised agent to production in minutes — zero infrastructure complexity

## Databases (architecture layer)

Persistent structured storage for agent state and outputs

- [Supabase](https://www.frameworkr.ai/tools/supabase.md): Open-source Firebase alternative — Postgres, auth, storage, and pgvector in one platform

## Monitoring & Observability (architecture layer)

Trace, evaluate, and debug agent runs in production

- [Helicone](https://www.frameworkr.ai/tools/helicone.md): Lightweight LLM proxy for logging, cost tracking, and caching with zero code changes
- [Langfuse](https://www.frameworkr.ai/tools/langfuse.md): Open-source LLM observability — trace every agent run, score outputs, and catch regressions

## MCP Servers (architecture layer)

Model Context Protocol servers that extend agent capabilities

- [Context7](https://www.frameworkr.ai/tools/context7.md): MCP server that injects up-to-date library documentation into your agent's context
- [Gemini CLI](https://www.frameworkr.ai/tools/gemini-cli.md): An open-source AI agent that brings the power of Gemini directly into your terminal.
- [MCP Filesystem Server](https://www.frameworkr.ai/tools/mcp-filesystem.md): Anthropic's reference MCP server for reading, writing, and navigating local filesystems