# Librefang Registry > Community-maintained content registry for LibreFang — agents, hands, integrations, skills, and provider models - **Type:** MCP server - **Install:** `agentstack add mcp-librefang-librefang-registry` - **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior - **Seller:** [librefang](https://agentstack.voostack.com/s/librefang) - **Installs:** 0 - **Category:** [AI & ML](https://agentstack.voostack.com/c/ai-and-ml) - **Latest version:** 0.1.0 - **License:** MIT - **Upstream author:** [librefang](https://github.com/librefang) - **Source:** https://github.com/librefang/librefang-registry ## Install ```sh agentstack add mcp-librefang-librefang-registry ``` Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent. ## About # LibreFang Registry Community-maintained content registry for [LibreFang](https://github.com/librefang/librefang) — the open-source Agent Operating System. This repository is the **single source of truth** for all installable content definitions. Anyone can submit a PR to add new agents, hands, MCP servers, skills, or provider models — no changes to the LibreFang binary required. ## Overview | Type | Count | Description | |------|------:|-------------| | [Hands](#hands) | 14 | User-facing "apps" — agent + tools + settings + dashboard | | [Agents](#agents) | 32 | Autonomous agent definitions with model config and tools | | [MCP Servers](#mcp-servers) | 25 | MCP server connections (GitHub, Slack, DBs, etc.) | | [Providers](#providers) | 46 | LLM provider & model metadata with pricing | | [Models](#providers) | 232 | Individual model definitions across all providers | | [Aliases](#aliases) | 70 | Short names mapped to canonical model IDs | | [Plugins](#plugins) | 10 | Memory, guardrails, and conversation plugins | | [Skills](#skills) | 2 | Reusable prompt templates and Python scripts | | [Workflows](#workflows) | 9 | Pre-built multi-agent workflow definitions | | [Templates](#templates) | 6 | Starter templates for each content type | ## Repository Structure ``` librefang-registry/ ├── agents/ # Agent definitions (TOML manifests) │ ├── hello-world/ │ │ └── agent.toml │ ├── researcher/ │ │ └── agent.toml │ └── ... (32 agents) ├── hands/ # Hand definitions (app bundles) │ ├── browser/ │ │ ├── HAND.toml # Metadata, tools, settings, i18n (6 languages) │ │ └── SKILL.md # Domain expert knowledge injected at runtime │ ├── trader/ │ │ ├── HAND.toml │ │ └── SKILL.md │ └── ... (14 hands) ├── mcp/ # MCP server templates │ ├── github.toml │ ├── slack.toml │ └── ... (25 MCP servers) ├── providers/ # LLM provider & model metadata │ ├── anthropic.toml │ ├── openai.toml │ └── ... (46 providers, 232 models) ├── plugins/ # Memory, guardrails, and utility plugins │ ├── episodic-memory/ │ ├── guardrails/ │ └── ... (10 plugins) ├── skills/ # Reusable skill definitions │ ├── custom-skill-prompt/skill.toml │ └── custom-skill-python/ ├── workflows/ # Pre-built multi-agent workflow definitions │ ├── code-review.toml │ ├── research.toml │ └── ... (9 workflows) ├── templates/ # Starter templates for each content type │ ├── agent.toml │ ├── HAND.toml │ └── ... (6 templates) ├── docs/ # Additional documentation │ └── content-guide.md # Content contribution guidelines ├── aliases.toml # Global model alias mappings (70 aliases) ├── schema.toml # Provider/model schema reference ├── scripts/ │ └── validate.py # Content validation script ├── CONTRIBUTING.md └── LICENSE # MIT ``` ## Content Types ### Hands Hands are the **user-facing "apps"** in LibreFang. Each hand bundles an agent, tools, user-configurable settings, dashboard metrics, dependency checks, and i18n translations into a single deployable unit. Every hand includes a `SKILL.md` — domain-specific expert knowledge that is injected into the agent's context at runtime, giving it deep expertise in its domain. | Icon | Hand | Category | Description | |:----:|------|----------|-------------| | 📈 | analytics | data | Data collection, analysis, visualization, dashboards, and automated reporting | | 🔌 | apitester | development | Endpoint discovery, request validation, load testing, and regression detection | | 🌐 | browser | productivity | Web navigation, form filling, and multi-step web tasks with user approval | | 🎬 | clip | content | Turns long-form video into viral short clips with captions and thumbnails | | 🔍 | collector | data | Intelligence collection, change detection, and knowledge graphs | | 👷 | devops | development | CI/CD management, infrastructure monitoring, deployment, and incident response | | 📊 | lead | data | Lead generation, enrichment, scoring, and scheduled delivery | | 💼 | linkedin | communication | Profile optimization, content creation, networking, and engagement | | 🔮 | predictor | data | Signal collection, calibrated predictions, and accuracy tracking | | 📢 | reddit | communication | Subreddit monitoring, content posting, and engagement tracking | | 🧪 | researcher | productivity | Deep research, cross-referencing, fact-checking, and structured reports | | 🎯 | strategist | productivity | Market research, competitive analysis, and strategic planning | | 📈 | trader | data | Multi-signal analysis, adversarial reasoning, and risk management | | 𝕏 | twitter | communication | Content creation, scheduled posting, engagement, and analytics | **HAND.toml format:** ```toml id = "browser" name = "Browser Hand" description = "Autonomous web browser" category = "productivity" icon = "🌐" tools = ["browser_navigate", "browser_click", "browser_type"] [routing] aliases = ["browse", "open website"] weak_aliases = ["web", "url"] [[requires]] key = "chromium" requirement_type = "binary" check_value = "chromium" [[settings]] key = "headless" setting_type = "toggle" default = "true" [agent] name = "browser-hand" module = "builtin:chat" system_prompt = """You are an autonomous web browser agent...""" [dashboard] [[dashboard.metrics]] label = "Pages Visited" memory_key = "pages_visited" format = "number" # i18n — 6 languages supported: zh, ja, ko, es, fr, de [i18n.zh] name = "浏览器 Hand" description = "自主网页浏览器" category = "生产力" [i18n.zh.settings.headless] label = "无头模式" description = "在后台运行浏览器" ``` ### Agents Agent definitions describe autonomous agents with model configuration, tools, capabilities, and routing aliases. ```toml name = "hello-world" description = "A friendly greeting agent" module = "builtin:chat" [model] provider = "default" model = "default" system_prompt = "You are a helpful assistant." [capabilities] tools = ["web_search", "file_read"] ``` **32 built-in agents:** academic-researcher, analyst, architect, assistant, code-reviewer, coder, customer-support, data-scientist, debugger, devops-lead, doc-writer, email-assistant, health-tracker, hello-world, home-automation, legal-assistant, meeting-assistant, ops, orchestrator, personal-finance, planner, recipe-assistant, recruiter, researcher, sales-assistant, security-auditor, social-media, test-engineer, translator, travel-planner, tutor, writer ### MCP Servers MCP server templates define [MCP](https://modelcontextprotocol.io/) server connections with transport configuration, required environment variables, and setup instructions. ```toml id = "github" name = "GitHub" category = "devtools" [transport] type = "stdio" command = "npx" args = ["-y", "@modelcontextprotocol/server-github"] [[required_env]] name = "GITHUB_PERSONAL_ACCESS_TOKEN" is_secret = true ``` **25 MCP servers across 6 categories:** | Category | MCP Servers | |----------|-------------| | DevTools | bitbucket, github, gitlab, jira, linear, sentry | | Data | elasticsearch, mongodb, postgresql, redis, sqlite | | Productivity | dropbox, gmail, google-calendar, google-drive, notion, todoist | | Communication | discord, slack, teams | | Cloud | aws, azure, gcp | | AI Search | brave-search, exa-search | ### Providers Provider files define LLM providers and their models with pricing, context windows, and capability flags. See [schema.toml](schema.toml) for the full field reference. **49 providers** including: Anthropic, OpenAI, Google Gemini, DeepSeek, Groq, Mistral, Cohere, xAI, Together, Fireworks, Ollama (local), LM Studio (local), vLLM (self-hosted), Alibaba Coding Plan, and many more. **339 models** with metadata for each: pricing (input/output per token), context window size, capability flags (vision, function calling, streaming), and tier classification. ### Aliases Global model alias mappings in [aliases.toml](aliases.toml) let users reference models by short names: ```toml "sonnet" = "claude-sonnet-4-6" "gpt4" = "gpt-4o" "flash" = "gemini-2.5-flash" "deepseek" = "deepseek-chat" ``` Models can also define aliases directly in their provider TOML files, which are auto-registered at load time. ### Plugins Plugins extend agent capabilities with memory systems, safety guardrails, and conversation utilities. **10 plugins:** auto-summarizer, context-decay, conversation-logger, episodic-memory, guardrails, keyword-memory, sentiment-tracker, todo-tracker, topic-memory, user-profile ### Skills Reusable prompt templates or Python scripts that agents can invoke. ```toml [skill] name = "meeting-agenda" description = "Generate a structured meeting agenda" [runtime] type = "promptonly" [prompt] template = "Create a meeting agenda for: {{topic}}" ``` ### Workflows Pre-built multi-agent workflow definitions in `workflows/.toml` orchestrate multiple agents for complex tasks. **9 workflows:** brainstorm, code-review, content-pipeline, content-review, customer-support, data-pipeline, research, translate-polish, weekly-report ### Templates Starter templates in `templates/` for creating new content. Copy a template to get started quickly: ```bash cp templates/agent.toml agents/my-agent/agent.toml cp templates/HAND.toml hands/my-hand/HAND.toml ``` **6 templates:** agent.toml, HAND.toml, integration.toml, plugin.toml, provider.toml, skill.toml See also [docs/content-guide.md](docs/content-guide.md) for naming conventions and contribution guidelines. ## Usage ### Install from Registry ```bash # Update all registry content librefang catalog update # Install a specific hand librefang hand install browser # Install a specific MCP server librefang mcp install github ``` ### Custom Local Content Create custom content locally without submitting to this registry: ```bash # Custom agent mkdir -p ~/.librefang/agents/my-agent # Edit ~/.librefang/agents/my-agent/agent.toml # Custom model aliases # Add to ~/.librefang/model_catalog.toml ``` ## Validation ```bash python scripts/validate.py ``` Validates all content files for correctness: required fields, valid types, non-negative costs, no duplicate IDs. ## Contributing 1. Fork this repository 2. Add or edit content in the appropriate directory 3. Run validation: `python scripts/validate.py` 4. Submit a Pull Request See [CONTRIBUTING.md](CONTRIBUTING.md) for detailed instructions for each content type. ## License MIT License. See [LICENSE](LICENSE). ## Source & license This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code. - **Author:** [librefang](https://github.com/librefang) - **Source:** [librefang/librefang-registry](https://github.com/librefang/librefang-registry) - **License:** MIT Install and usage instructions live in the source repository linked above. ## Pricing - **Free** — Free ## Security capabilities Automated source analysis of v0.1.0 — what this tool can access: - **Network access:** no - **Filesystem access:** no - **Shell / process execution:** no - **Environment & secrets:** no - **Dynamic code execution:** no *"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.* ## Versions - **0.1.0** — security scan: passed — Imported from the upstream source. ## Links - Listing page: https://agentstack.voostack.com/l/mcp-librefang-librefang-registry - Seller: https://agentstack.voostack.com/s/librefang - Browse the marketplace: https://agentstack.voostack.com/browse --- Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.