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Mcpc

mcp-mcpc-tech-mcpc · by mcpc-tech

Build agentic-MCP servers by composing existing MCP tools.

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Install

$ agentstack add mcp-mcpc-tech-mcpc

✓ 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.

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About

MCPC

[](https://jsr.io/@mcpc/core) [](https://www.npmjs.com/package/@mcpc-tech/core)

Build agentic MCP servers by composing existing MCP tools.

MCPC is the SDK for building agentic MCP (Model Context Protocol) Servers. You can use it to:

  1. Create Powerful Agentic MCP Tools: Simply describe your vision in text

and reference tools from the expanding MCP community. As standard MCP tools, your agents work everywhere and collaborate seamlessly.

  1. Fine-Tune Existing Tools: Flexibly modify existing tool descriptions and

parameters, or wrap and filter results to precisely adapt them to your specific business scenarios.

  1. Build Multi-Agent Systems: By defining each agent as a MCP tool, you can

compose and orchestrate them to construct sophisticated, collaborative multi-agent systems.

Key Features

  • Portability and agent interoperability: Build once, run everywhere as MCP

tools - agents work across all MCP clients and can discover and collaborate with each other through standard MCP interfaces

  • Simple composition and fine-tuning: Compose MCP servers as building

blocks, select and customize tools, or modify their descriptions and parameters

  • Logging and tracing: Built-in MCP logging and OpenTelemetry tracing

support

  • Skills support: Define domain-specific knowledge following the

Agent Skills specification - deploy to production, share via MCP, and declare tool dependencies

  • Flexible execution modes: Multiple specialized modes to fit different

scenarios - interactive agent (agentic), AI SDK sampling (ai_sampling), AI ACP mode (ai_acp), secure code execution ([code_execution](packages/plugin-code-execution/)), and sandbox + sampling ([code_execution_sampling](packages/plugin-code-execution-sampling/)) - each with dedicated implementations

Quick Start

Three Ways to Get Started

1. Use the Website (Fastest)

Visit mcpc.tech to browse servers from the official MCP registry, discover tools, and generate ready-to-use agents.

2. Use the Agent (Interactive)

Let AI help you discover servers and build agents:

Add to your MCP client:

{
  "mcpServers": {
    "mcpc-builder-agent": {
      "command": "npx",
      "args": ["-y", "@mcpc-tech/builder", "mcpc-builder-agent"]
    }
  }
}
3. Write Code (Full Control)

Use the SDK directly for complete customization. See examples below.


Installation

# npm (from npm registry)
npm install @mcpc-tech/core
# npm (from jsr)
npx jsr add @mcpc/core

# deno
deno add jsr:@mcpc/core

# pnpm (from npm registry)
pnpm add @mcpc-tech/core
# pnpm (from jsr)
pnpm add jsr:@mcpc/core

Or run directly with the CLI (no installation required):

# Run with remote configuration
npx -y @mcpc-tech/cli --config-url \
  "https://raw.githubusercontent.com/mcpc-tech/mcpc/main/packages/cli/examples/configs/codex-fork.json"

Examples: Create a Simple Codex/Claude Code Fork

import { mcpc } from "@mcpc/core";

const server = await mcpc(
  [{ name: "coding-agent", version: "0.1.0" }, { capabilities: { tools: {} } }],
  [{
    name: "coding-agent",
    description: `
      You are a coding assistant with advanced capabilities.

      Your capabilities include:
      - Reading and writing files
      - Executing terminal commands to build, test, and run projects
      - Interacting with GitHub to create pull requests and manage issues

      Available tools:
      
      
      
      
    `,
    deps: {
      mcpServers: {
        "desktop-commander": {
          command: "npx",
          args: ["-y", "@wonderwhy-er/desktop-commander@latest"],
          transportType: "stdio",
        },
        github: {
          transportType: "streamable-http",
          url: "https://api.githubcopilot.com/mcp/",
        },
      },
    },
  }],
);

> Complete Example: See the full > [Codex fork tutorial](docs/examples/creating-a-codex-fork.md).

Install the MCPC Core Skill

Install the mcpc-core skill into your project using skills.sh:

npx skills add mcpc-tech/mcpc

This installs the skill into .agents/skills/mcpc-core/, giving your agent on-demand access to the full @mcpc/core API reference, usage patterns, plugin guide, and gotchas.


Examples: Load Agent Skills

For complex agents where inline description becomes unwieldy, use Agent Skills to organize domain knowledge in separate files that are loaded on-demand.

import { createBashPlugin, createSkillsPlugin } from "@mcpc/core/plugins";

const server = await mcpc(
  [{ name: "my-agent", version: "1.0.0" }, { capabilities: { tools: {} } }],
  [{
    name: "my-agent",
    description: 'An agent with domain knowledge\n\n',
    plugins: [
      createSkillsPlugin({ paths: ["./skills"] }),
      createBashPlugin(),
    ],
  }],
);

Skills load domain knowledge on-demand, while bash plugin enables script execution. For scripts in scripts/ directory, skills returns the path - use bash tool to execute.

> Complete Examples: See > [14-skills-plugin.ts](packages/core/examples/14-skills-plugin.ts) and > [25-skills-with-bash.ts](packages/core/examples/25-skills-with-bash.ts).

Examples: Progressive Manual Disclosure

For agents with detailed instructions, use the manual field to reduce initial prompt length - the full manual is fetched on-demand via man { manual: true }:

const server = await mcpc(
  [{ name: "code-reviewer", version: "1.0.0" }, {
    capabilities: { tools: {} },
  }],
  [{
    name: "code-reviewer",
    description: "AI code reviewer for quality and security analysis.",
    manual: `Detailed review guidelines...

## Review Categories
1. Code Quality - readability, naming, complexity
2. Security - SQL injection, XSS, credentials
...`,
    deps: {
      mcpServers: {
        "desktop-commander": {
          command: "npx",
          args: ["-y", "@wonderwhy-er/desktop-commander@0.1.20"],
          transportType: "stdio",
        },
      },
    },
  }],
);

> Complete Example: See > [21-progressive-manual.ts](packages/core/examples/21-progressive-manual.ts).

How It Works

Three simple steps:

  1. Define dependencies - List the MCP servers you want to use
  2. Write agent description - Describe what your agent does and reference

tools

  1. Create server - Use mcpc() to build and connect your server

Execution Modes

MCPC provides multiple flexible execution modes to fit different scenarios:

| Mode | Description | Use Case | Requires Plugin | | ------------------------- | --------------------------------------------- | ---------------------------------------------------- | --------------- | | agentic | Interactive step-by-step execution | Standard agent interactions | Built-in | | ai_sampling | AI SDK sampling mode | Autonomous AI SDK execution | Built-in | | ai_acp | AI SDK ACP mode | Coding agents (Claude Code, etc.) | Built-in | | code_execution | Secure JavaScript sandbox with tool access | Code generation and execution | External | | code_execution_sampling | Secure sandbox plus MCP sampling-backed calls | Sandbox execution that can also ask the client model | External |

> Note: agentic, ai_sampling, and ai_acp are built-in modes — just set > options.mode and they work. code_execution and code_execution_sampling > require installing and loading their respective plugin packages.

Quick Example

// Interactive agent (default)
{ options: { mode: "agentic" } }

// Autonomous agent
{ options: { mode: "ai_sampling", samplingConfig: { maxIterations: 10 } } }

// Code execution with sandbox
import { createCodeExecutionPlugin } from "@mcpc/plugin-code-execution/plugin";
{
  plugins: [createCodeExecutionPlugin()],
  options: { mode: "code_execution" }
}

> Detailed Documentation: See > [Execution Modes Guide](docs/execution-modes.md) for comprehensive information > on each mode, configuration options, and best practices.

Documentation

  • [Getting Started](docs/quickstart/installation.md) - Installation and

first steps

  • [Creating Your First Agent](docs/quickstart/create-your-first-agentic-mcp.md) -

Complete tutorial

  • [Execution Modes](docs/execution-modes.md) - Comprehensive guide to all

execution modes

  • [CLI Usage Guide](docs/quickstart/cli-usage.md) - Using the MCPC CLI
  • [Logging and Tracing](docs/logging-and-tracing.md) - MCP logging and

OpenTelemetry tracing

  • [Examples](docs/examples/) - Real-world use cases
  • [FAQ](docs/faq.md) - Common questions and answer

Examples

See working examples in the [examples directory](packages/core/examples/) or check out the [Codex fork tutorial](docs/examples/creating-a-codex-fork.md).

Contributing

We welcome contributions! See [CONTRIBUTING.md](CONTRIBUTING.md) for details.

License

MIT License - see [LICENSE](LICENSE) for details.

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.