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MCP verified MIT Self-run

Pi T3chat

mcp-vibheksoni-pi-t3chat · by vibheksoni

pi-t3chat t3.chat extension for Pi coding agent. 50+ frontier AI models (Claude Fable-5, GPT-5.6, Gemini 3.5, Grok 4.3, DeepSeek V4, Llama 4, Qwen 3) via t3.chat subscription. TLS impersonation, dynamic model discovery, tool calling, MCP wrapper tools.

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Install

$ agentstack add mcp-vibheksoni-pi-t3chat

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

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Reliability & compatibility

Security review passed
0 installs to date
no reviews yet
1mo ago

Declared compatibility

Claude CodeClaude DesktopCursorWindsurf

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

Preview Execution monitoring

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About

pi-t3chat running in Pi — 50+ frontier models via t3.chat subscription

pi-t3chat

t3.chat models in Pi — 50+ frontier AI models via your t3.chat subscription

[](https://github.com/vibheksoni/pi-t3chat) [](https://opensource.org/licenses/MIT) [](#models) [](#tls-impersonation)

Claude Fable-5 · GPT-5.6 · Gemini 3.5 · Grok 4.3 · DeepSeek V4 · Llama 4 · Qwen 3 · 50+ more


Overview

pi-t3chat is a Pi coding agent extension that bridges t3.chat's multi-model API into Pi's OpenAI-compatible provider interface. It spins up a local proxy that translates OpenAI Chat Completions calls to t3.chat's SSE streaming format — with full TLS fingerprint impersonation, dynamic model discovery, text-based tool calling, and MCP wrapper tool discovery.

How It Works

Pi  →  Local Proxy (127.0.0.1:42101)  →  t3.chat API (https://t3.chat/api/chat)
         OpenAI-compatible HTTP           SSE streaming with TLS impersonation

The extension spins up a local HTTP proxy that translates OpenAI Chat Completions API calls to t3.chat's SSE format. All requests to t3.chat use wreq-js for TLS fingerprint impersonation (Chrome 142) — standard fetch() gets blocked by t3.chat's bot detection.

Features

  • 50+ frontier AI models — Claude, GPT, Gemini, Grok, DeepSeek, Llama, Qwen, and more through a single t3.chat subscription
  • Dynamic model discovery — scrapes t3.chat's JS bundles to fetch model definitions; zero hardcoding
  • TLS fingerprint impersonation — wreq-js with Chrome 142 emulation bypasses t3.chat's bot detection
  • Text-based tool calling — injects tool definitions as text; model emits tool: fenced blocks; proxy converts to OpenAI tool_calls
  • MCP wrapper toolsmcp__ prefixed tools are grouped into MCP servers with list_mcps / list_mcp_tools / call_mcp discovery protocol
  • False refusal correction — auto-retries when the model claims it "can't access tools" while tools are available
  • Credit tracking — real-time balance, usage percentages, and subscription tier via tRPC endpoints
  • Cookie-based auth — no API keys; uses your existing t3.chat browser session

Tool Calling

t3.chat models don't all support OpenAI-native function calling. This extension implements a text-based tool calling protocol:

  1. Injection — OpenAI tool definitions are injected into the system prompt as text instructions
  2. Emission — The model emits tool: fenced code blocks in its response
  3. Parsing — The proxy parses these blocks and converts them to OpenAI tool_calls format
  4. False refusal correction — If the model claims it "can't access tools" while tools are available, the proxy automatically retries with a correction prompt (up to 2 retries)

Example tool block emitted by the model:

````

```tool:read_file {"path": "/src/index.ts"}

````

For models that support native tool calling via the SSE stream, the proxy also handles structured `tool_calls` deltas.

### MCP Wrapper Tools

Tools with `mcp__` prefixes (e.g. `mcp__exa__web_search`) are automatically grouped into MCP servers. Instead of injecting all MCP tool definitions into the system prompt, the proxy injects three wrapper tools:

- **`list_mcps`** — List all available MCP groups
- **`list_mcp_tools`** — List tools within one MCP group
- **`call_mcp`** — Execute a specific MCP tool by group + tool name

The model discovers tools on-demand through a multi-round loop (max 6 rounds), reducing prompt size dramatically when many MCP tools are available.

## Installation

### Git (recommended)

```bash
pi extension add https://github.com/vibheksoni/pi-t3chat.git

Local dev

git clone https://github.com/vibheksoni/pi-t3chat.git
cd pi-t3chat
pi extension add .

Setup

  1. Sign in to t3.chat in your browser
  2. Open DevTools → Application → Cookies → t3.chat
  3. Run /login t3chat in Pi
  4. Paste your full Cookie header string
  5. Paste your convex-session-id value
  6. Select a model with /model t3chat/

Commands

| Command | Description | |---------|-------------| | /login t3chat | Sign in using t3.chat cookies | | t3chat-status | Show auth status, credits, and subscription | | t3chat-logout | Sign out and clear stored credentials | | t3chat-refresh | Refresh model catalog from t3.chat |

Models

Models are fetched dynamically by scraping t3.chat's JavaScript bundles — zero hardcoding. The catalog is cached for 10 minutes and refreshed on demand.

Run t3chat-refresh after new models are added to t3.chat.

Notable Models

| Model | Description | |-------|-------------| | claude-fable-5 | Anthropic's autonomous knowledge work model | | sonoma-dusk-alpha | 2M token context window | | fast | Efficient open model | | 50+ more | Anthropic, Google, OpenAI, xAI, DeepSeek, Meta, Alibaba, Xiaomi, MiniMax, Moonshot, GLM, InclusionAI |

TLS Impersonation

t3.chat blocks requests with non-browser TLS fingerprints. This extension uses wreq-js — a Node.js/TypeScript HTTP client powered by native Rust wreq bindings — to impersonate Chrome 142's TLS/JA3/HTTP2 fingerprint on every request.

File Structure

pi-t3chat/
├── index.ts     — Pi extension entry point, provider registration, commands
├── proxy.ts     — OpenAI-compatible HTTP proxy → t3.chat SSE
├── chat.ts      — t3.chat SSE streaming via wreq-js
├── sse.ts       — SSE stream parser for t3.chat events
├── tools.ts     — Text-based tool calling protocol (injection, parsing, correction)
├── mcp.ts       — MCP wrapper tools (list_mcps / list_mcp_tools / call_mcp)
├── catalog.ts   — Model discovery by scraping t3.chat JS bundles
├── models.ts    — Model resolution (name → ID lookup)
├── usage.ts     — Credit tracking via tRPC endpoints
├── auth.ts      — Cookie-based credential storage
├── config.ts    — Chat config options
└── package.json — Package metadata

Endpoints Used

| URL | Method | Purpose | |-----|--------|---------| | /api/chat | POST | Chat message (SSE stream) | | /api/trpc/getCustomerData | GET | Credit balance, usage % | | /api/trpc/getSubscriptionData | GET | Subscription tier | | /api/trpc/getPricingProducts | GET | Pricing tiers | | /api/trpc/getModelStatuses | GET | Model operational status | | /api/trpc/getAllModelBenchmarks | GET | Model benchmark scores | | /api/trpc/auth.getActiveSessions | GET | Active browser sessions | | /api/status | GET | Deployment status |

License

MIT

Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

Reviews

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Versions

  • v0.1.0 Imported from the upstream source.