f2g-telco

F2G-Telco

CLI to set up a fully configured AI coding environment in one command—MCPs, providers, skills, orchestrators, and inventories for Crush and Kiro.

Install

npx f2g-telco init

What You Get

• 13 MCP servers for memory, knowledge, reasoning, browser automation, diagrams, GitHub, databases
• Curated skills from multiple sources with orchestrator templates
• Provider-agnostic configs for Copilot, Ollama, NVIDIA NIM, Google AI Studio, and any OpenAI-compatible API
• Complete tool wiring: MCPs, providers, models, permissions, LSPs, orchestrator agent, INVENTORY.md

Why F2G-Telco vs. Manual Setup

Step	f2g-telco	Manual setup
Install MCP servers	Auto-installs with user prefix and fallbacks	Repeated npm/pip commands, sudo issues
Tool config	Writes full Crush/Kiro configs (MCPs, providers, models, permissions, LSP)	Hand-edit JSON with multiple schemas
Skills & orchestrator	Clones, symlinks, and wires orchestrator templates	Manual git clone + path wiring
Provider keys	Guided boxed prompts with skip/retry	Ad hoc env collection
Inventory	Generates INVENTORY.md for agents	Manual docs
Recovery	Verbose mode + doctor checks	Debug on your own

Command Reference

Command	Description
f2g-telco init	Interactive setup wizard (tools, providers, MCPs, skills, configs)
f2g-telco add <mcp>	Install and configure a single MCP by id
f2g-telco remove <mcp>	Uninstall and remove a single MCP by id
`f2g-telco list [--mcps	--providers
f2g-telco update	Pull latest registries and refresh configs
f2g-telco doctor	Health check (Node, git, PATH, MCP binaries)

Providers

Provider	Free?	Models	Description
GitHub Copilot	Subscription	Claude Opus/Sonnet/Haiku, GPT, Gemini, Grok	Full catalog via Copilot
Ollama	✅ Free	Qwen3, Llama, Mistral, etc.	Local models, private
NVIDIA NIM	✅ Free tier	Llama 3.3 70B, DeepSeek R1, Kimi K2.5	1000 free credits
Google AI Studio	✅ Free tier	Gemini 2.5 Pro/Flash	Free key from aistudio.google.com
Groq	✅ Free tier	Llama 3.3 70B, Llama 3.1 8B	Ultra-fast inference
Cerebras	✅ Free tier	Llama 3.3 70B, Llama 3.1 8B	Fastest inference, 30 req/min
OpenAI-Compatible	Varies	Any compatible model	LM Studio, vLLM, custom endpoints

MCP Servers Included

Server	Category	Free	Description
mem0	Memory	✅	Long-term memory across sessions
contextgraph	Memory	✅	Shared memory with provenance + entities
memory	Memory	✅	Knowledge graph — entities and relations
context7	Knowledge	✅	Up-to-date library documentation
sequential-thinking	Reasoning	✅	Multi-step reasoning with branching
filesystem	Core	✅	File operations
fetch	Core	✅	HTTP requests
github	Dev	✅	PRs, issues, commits
gitnexus	Dev	✅	Codebase knowledge graph
postgresql	Dev	✅	Database queries
playwright	Testing	✅	Browser automation, E2E
mermaid	Docs	✅	Diagram rendering
notion	Productivity	✅	Notion pages and databases

What Gets Configured

Crush

• MCP servers with env vars
• Providers and model mappings (large/small)
• Permissions (38+ tools auto-approved)
• LSP servers (pyright, typescript-language-server)
• Skills paths, orchestrator agent, metrics/notifications off

Kiro

• MCP servers with autoApprove arrays
• Env vars per MCP, orchestrator settings

Contributing

Pull requests are welcome. Please run npm run build and npm test before submitting.

License

MIT