The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.
Pctx
Pctx is the execution layer for agentic tool calls. It auto-converts agent tools and MCP servers into code that runs in secure sandboxes for token-efficient workflows.
Install
pip install pctx-clientInstall command taken from the project's README or registry entry. Always review code before running it.
README excerpt
Read full README on GitHub →pctx
The open source framework to connect AI agents to tools and mcp with Code Mode
— T R U S T E D B Y —
Install
# 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
Core Functionality
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
Python SDK
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,
)
Links
Node SDK
Coming soon
Unified MCP
Use the unified MCP to run Code Mode with MCP servers and want to persist the authentication connections and you do not need to use agent tools (non-mcp tools).
# Initialize config for upstream mcp connections
pctx mcp init
# Add HTTP or stdio MCP servers
pctx mcp add stripe https://mcp.stripe.com
pctx mcp add memory --command "npx -y @modelcontextprotocol/server-memory"
# Start as HTTP server (dev mode with UI)
pctx mcp dev
# Or start as stdio MCP server
pctx mcp start --stdio
For complete CLI documentation, see CLI.md. For configuration options, see Configuration Guide.
What is pctx?
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.
What is Code Mode?
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:
- Agent calls
getSheet(id) - Server returns 1000 rows → agent's context
- Agent calls
filterRows(criteria) - 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.
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