haive-mcp 1.0.1

Dynamic MCP integration for AI agents - search 1,960+ servers, install with HITL approval, connect via LangChain or Docker

haive-mcp

Dynamic MCP integration for AI agents — search 1,960+ servers, install with HITL approval, connect via LangChain or Docker.

haive-mcp enables runtime discovery and integration of tools from the Model Context Protocol (MCP) ecosystem. Instead of hard-coding tool integrations, your agents can search the MCP registry, install relevant servers (with human approval), and use them as standard LangChain tools.

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What is MCP?

Model Context Protocol is Anthropic's open standard for connecting LLM applications to external tools and data sources. There are 1,960+ MCP servers covering everything from databases to file systems to GitHub APIs to browser automation.

haive-mcp is the bridge between MCP and the Haive agent framework. It provides:

1. Server discovery — search across the entire MCP registry by capability
2. Multiple transports — STDIO (npx/uvx), SSE, Streamable HTTP, Docker
3. HITL approval — Human-in-the-loop gating for server installation
4. LangChain bridge — MCP tools work as standard LangChain tools
5. Docker isolation — run servers in containers for security
6. Intelligent agent — IntelligentMCPAgent auto-discovers tools for tasks

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Why dynamic MCP?

Static tool libraries are limiting. You either:

• Pre-install tools you might never need (bloat)
• Don't have a tool when you need it (hard-coded constraint)

Dynamic MCP integration: Your agent has access to 1,960+ servers on demand. Need to query a database? It finds and installs mcp/postgres. Need to scrape a website? It pulls playwright-mcp. Need GitHub access? github-mcp-server. With HITL approval gates so the user controls what gets installed.

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Installation

pip install haive-mcp

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Transport Types

MCP servers communicate over different transports. haive-mcp supports all four:

Transport	Value	Use Case	Example
STDIO	stdio	CLI servers via npx/uvx (most common)	npx @modelcontextprotocol/server-filesystem
SSE	sse	HTTP streaming servers	Long-running services
Streamable HTTP	streamable_http	Continuous data	Real-time feeds
Docker	docker	Isolated containers	Untrusted servers, complex deps

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Usage Patterns

1. Static Configuration

Hand-pick servers and configure them upfront:

from haive.mcp.config import MCPConfig, MCPServerConfig, MCPTransport
from haive.mcp.manager import MCPManager

config = MCPConfig(
    enabled=True,
    servers={
        "filesystem": MCPServerConfig(
            name="filesystem",
            transport=MCPTransport.STDIO,
            command="npx",
            args=["-y", "@modelcontextprotocol/server-filesystem", "/workspace"],
        ),
        "github": MCPServerConfig(
            name="github",
            transport=MCPTransport.STDIO,
            command="npx",
            args=["-y", "@modelcontextprotocol/server-github"],
            env={"GITHUB_PERSONAL_ACCESS_TOKEN": "ghp_..."},
        ),
        "postgres": MCPServerConfig(
            name="postgres",
            transport=MCPTransport.DOCKER,
            command="mcp/postgres",
            env={"POSTGRES_HOST": "host.docker.internal"},
            docker_volumes=["/data:/data:ro"],
            docker_network="host",
        ),
    }
)

# Connect and get tools
manager = MCPManager(config)
await manager.connect_all()
tools = await manager.get_all_tools()

# Use with any Haive agent
from haive.agents.react.agent import ReactAgent
from haive.core.engine.aug_llm import AugLLMConfig

agent = ReactAgent(
    engine=AugLLMConfig(tools=tools),
    max_iterations=5,
)
result = await agent.arun("List files in /workspace and create a summary issue on GitHub")

2. Dynamic Discovery (IntelligentMCPAgent)

Let the agent discover and install tools as needed:

from haive.mcp.agents import IntelligentMCPAgent
from haive.core.engine.aug_llm import AugLLMConfig

agent = IntelligentMCPAgent(
    engine=AugLLMConfig(),
    auto_discover=True,        # Search registry for relevant servers
    require_approval=True,      # HITL approval before installing
)

result = await agent.arun(
    "Find Python repositories on GitHub about quantum computing"
)
# Agent flow:
# 1. Searches MCP registry for "github"
# 2. Finds github-mcp-server
# 3. Asks for approval to install
# 4. Installs via npx
# 5. Connects to server
# 6. Calls github_search_repositories tool
# 7. Returns results

3. CLI

Manage MCP servers from the command line:

# Install the CLI (comes with haive-mcp)
pip install haive-mcp

# Discover servers
haive-mcp discover "database"
haive-mcp discover "web scraping"
haive-mcp discover "github"

# List available transports
haive-mcp transports

# Install a specific server
haive-mcp install postgres

# Test a server
haive-mcp test filesystem

# Show server tools
haive-mcp tools filesystem

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HITL Approval Flow

When require_approval=True, the agent pauses and asks before installing any new server:

🔍 Searching MCP registry for 'database'...
✅ Found: postgres-mcp (mcp/postgres)
   Description: PostgreSQL database access via MCP
   Tools: query, schema, list_tables, describe_table
   Transport: stdio
   Trust: ⭐⭐⭐⭐⭐ (1.2k installs)

❓ Install postgres-mcp? [y/N]: y
📦 Installing via npx...
✅ Installed and connected
🔧 Available tools: query, schema, list_tables, describe_table

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Architecture

┌─────────────────────────────────────────────────┐
│              IntelligentMCPAgent                │
│  (auto_discover + HITL approval)                │
└────────────────────┬────────────────────────────┘
                     │
        ┌────────────┴────────────┐
        ▼                         ▼
┌──────────────┐          ┌──────────────┐
│  Discovery   │          │   MCPMgr     │
│              │          │              │
│ • Search     │          │ • Lifecycle  │
│ • Documentation│        │ • Connection │
│ • 1960+ servers│        │ • Tools      │
└──────────────┘          └──────┬───────┘
                                 │
                ┌────────────────┼────────────────┐
                ▼                ▼                ▼
        ┌─────────────┐  ┌─────────────┐  ┌─────────────┐
        │   STDIO     │  │     SSE     │  │   Docker    │
        │  npx/uvx    │  │   HTTP      │  │  Container  │
        └─────────────┘  └─────────────┘  └─────────────┘

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Documentation

📖 Full documentation: https://pr1m8.github.io/haive-mcp/

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Related Packages

Package	Description
haive-core	Foundation: engines, graphs
haive-agents	Production agents (use MCP tools)
haive-tools	Static tool implementations

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License

MIT © pr1m8