pctx

# Homebrew
brew install portofcontext/tap/pctx

# cURL
curl --proto '=https' --tlsv1.2 -LsSf https://raw.githubusercontent.com/portofcontext/pctx/main/install.sh | sh

# npm
npm i -g @portofcontext/pctx

pctx can be run as a stateless HTTP server for Code Mode sessions or as a unified MCP server that exposes Code Mode functionality for registered upstream MCP servers.

# Start Code Mode for Python SDK
pctx start

# Start Code Mode as a unified MCP server
pctx mcp init
pctx mcp dev

Use the Python SDK if building agents in Python and want to run Code Mode with custom tools and/or MCP servers. The Python SDK is an HTTP client to the pctx server.

pip install pctx-client

from pctx_client import Pctx, tool
from agents import Agent # Use any Agent SDK
from agents.run import Runner # This example is OpenAI Agents SDK

@tool
def get_weather(city: str) -> str:
    """Get weather information for a given city."""
    return f"It's always sunny in {city}!"

pctx = Pctx(tools=[get_weather]) # or with mcp: servers=[your_mcp]

tools = pctx.openai_agents_tools() # Run Code Mode with any Agent SDK
agent = Agent(
    name="GreatCoder",
    model="litellm/openrouter/openai/gpt-oss-120b",
    instructions="You run code to complete complex tasks.",
    tools=tools,
)

• Python SDK Quickstart and Docs
• Python API Reference

Coming soon

Use the unified MCP to run Code Mode with MCP servers and want to persist the authentication connections and you do not need to register local tools.

# Initialize config for upstream mcp connections
pctx mcp init

# Connect to any MCP server
pctx mcp add my-local-server http://localhost:3000/mcp
pctx mcp add stripe https://mcp.stripe.com

# Start the unified MCP server in dev mode
pctx mcp dev

# copy server url and connect to agents with --transport http

For complete CLI documentation, see CLI.md. For configuration options, see Configuration Guide.

pctx sits between AI agents and MCP servers. It aggregates multiple upstream MCP servers, handles authentication, and exposes tools through a unified Code Mode interface. Instead of agents managing connections to individual MCP servers, they connect once to pctx.

Code mode replaces sequential tool calling with code execution. Rather than an agent calling tools one at a time and passing results through its context window, it writes code that executes in a sandbox. Read Anthropic's overview here.

Traditional MCP flow:

1. Agent calls getSheet(id)
2. Server returns 1000 rows → agent's context
3. Agent calls filterRows(criteria)
4. Server returns 50 rows → agent's context

With Code Mode:

const sheet = await gdrive.getSheet({ sheetId: "abc" });
const orders = sheet.filter((row) => row.status === "pending");
console.log(`Found ${orders.length} orders`);

Result: 98.7% reduction in tokens (150k → 2k) for this multi-step operation.

• Code Mode interface: Tools exposed as code functions for efficient agent interaction. See Code Mode Guide.
• Upstream MCP server aggregation: Connect to multiple MCP servers through a single interface. See Upstream MCP Servers Guide.
• Simple config with CLI: Create the pctx.json config with a simple CLI. pctx.json manages auth, upstream MCPs, logging, and more. See Config Guide.
• Secure authentication: Source secrets from environment variables, system keychain, and external commands. See Authentication Section in the CLI configuration docs for more details.

• LLM generated code runs in an isolated Deno sandbox that can only access the network hosts specified in the configuration file.
• No filesystem, environment, network (beyond allowed hosts), or system access.
• MCP clients are authenticated in pctx. LLMs can never see your auth.

Depending on the installation method (Homebrew/npm/cURL) the update method is different. Run which pctx if you are unsure what you used to install it.

# Homebrew update
brew upgrade pctx

# cURL update
pctx-update

# npm update
npm upgrade -g @portofcontext/pctx

• Model Context Protocol (MCP)
• Code execution with MCP by Anthropic
• Code Mode explanation by Cloudflare