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Plivo provides an MCP server that allows AI assistants to search our documentation. Use it to get accurate, contextual answers about Plivo APIs, SDKs, and features directly in your development environment. MCP Server URL: https://plivo.com/docs/mcp

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What is MCP?

The Model Context Protocol (MCP) is an open standard that lets AI applications connect to external tools and data sources. By connecting your AI assistant to Plivo’s MCP server, it can search our documentation and provide accurate answers with direct links to relevant pages.

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Available Tools

ToolDescription
SearchPlivoSearch across the Plivo knowledge base to find relevant information, code examples, API references, and guides

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Setup by Client

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Claude Desktop

Add to your Claude Desktop config file: macOS: ~/Library/Application Support/Claude/claude_desktop_config.json Windows: %APPDATA%\Claude\claude_desktop_config.json 
{
  "mcpServers": {
    "plivo": {
      "command": "npx",
      "args": ["-y", "mcp-remote", "https://plivo.com/docs/mcp"]
    }
  }
}
Restart Claude Desktop after saving.

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Claude Code (CLI)

claude mcp add plivo --transport http https://plivo.com/docs/mcp

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Cursor

Go to Settings → MCP Servers and add: 
{
  "mcpServers": {
    "plivo": {
      "command": "npx",
      "args": ["-y", "mcp-remote", "https://plivo.com/docs/mcp"]
    }
  }
}

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Cline (VS Code)

Open Cline settings and add to MCP configuration: 
{
  "plivo": {
    "command": "npx",
    "args": ["-y", "mcp-remote", "https://plivo.com/docs/mcp"]
  }
}

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Windsurf

Add to your MCP configuration: 
{
  "mcpServers": {
    "plivo": {
      "command": "npx",
      "args": ["-y", "mcp-remote", "https://plivo.com/docs/mcp"]
    }
  }
}

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Using with OpenAI or Gemini

OpenAI and Google Gemini don’t natively support MCP, but you can use MCP-compatible clients that support multiple models:

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Option 1: Use Cursor or Cline

Both Cursor and Cline support MCP and allow you to switch between Claude, GPT-4, and Gemini models:
  1. Configure the MCP server as shown above
  2. Change your model to GPT-4o or Gemini in the client settings
  3. The client bridges MCP tools to the model’s function calling

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Option 2: Direct API Integration

Call the MCP endpoint directly and include the results in your prompt: 
import requests
import openai  # or google.generativeai

# Search Plivo documentation
response = requests.post(
    "https://plivo.com/docs/mcp",
    json={
        "jsonrpc": "2.0",
        "method": "tools/call",
        "params": {
            "name": "SearchPlivo",
            "arguments": {"query": "audio streaming websocket"}
        },
        "id": 1
    }
)
docs_context = response.json()

# Use with OpenAI
completion = openai.chat.completions.create(
    model="gpt-4o",
    messages=[
        {"role": "system", "content": f"Answer using this context:\n{docs_context}"},
        {"role": "user", "content": "How do I set up audio streaming with Plivo?"}
    ]
)
print(completion.choices[0].message.content)

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Option 3: LangChain Integration

from langchain_mcp import MCPToolkit
from langchain_openai import ChatOpenAI

toolkit = MCPToolkit(server_url="https://plivo.com/docs/mcp")
tools = toolkit.get_tools()

llm = ChatOpenAI(model="gpt-4o").bind_tools(tools)
response = llm.invoke("How do I make an outbound call with Plivo?")

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Example Queries

Once connected, try asking your AI assistant:
  • “How do I make an outbound call with Plivo in Python?”
  • “What are the audio streaming WebSocket message formats?”
  • “Show me how to set up a Pipecat voice agent”
  • “What XML elements can I use for IVR?”
  • “How do I handle incoming SMS messages?”
The AI will search Plivo documentation and provide accurate answers with links to the relevant pages.

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Troubleshooting

IssueSolution
”MCP server not found”Ensure you have Node.js installed and npx is available in your PATH
Connection timeoutCheck your network connection and firewall settings
No search resultsTry rephrasing your query with different keywords
Tool not appearingRestart your AI client after configuration changes