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dialgoodian/clawdcall-mcp

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[](https://glama.ai/mcp/servers/dialgoodian/clawdcall-mcp) ๐ŸŽ–๏ธ ๐Ÿ“‡ โ˜๏ธ - Let AI agents place consent-based outbound phone calls and retrieve transcripts, summaries, and outcomes. Use

MCP

dialgoodian/clawdcall-mcp

Added 8 Sept 2026

Overview

Clawdcall MCP is a Model Context Protocol server that lets AI agents place outbound phone calls with explicit consent. It provides access to call transcripts, summaries, and outcomes, enabling voice-based interactions within agent workflows.

Best for

Best for
Developers building AI agents that need to make consent-based phone calls and process the resulting conversation data.

Use cases

  • Trigger a phone call from an AI agent and retrieve the resulting transcript
  • Automate follow-up calls and capture summarized outcomes for downstream processing
  • Integrate consent-based voice communication into existing MCP-compatible agent pipelines

Notes

Clawdcall MCP is a Model Context Protocol server that lets AI agents place outbound phone calls with explicit consent. It provides access to call transcripts, summaries, and outcomes, enabling voice-based interactions within agent workflows.

0 stars on GitHub. Last updated 2026-09-06. Licensed MIT.

Use cases

  • Trigger a phone call from an AI agent and retrieve the resulting transcript
  • Automate follow-up calls and capture summarized outcomes for downstream processing
  • Integrate consent-based voice communication into existing MCP-compatible agent pipelines

Pros

  • Enables direct voice communication from AI agents without custom telephony code
  • Emphasizes consent, aligning with responsible calling practices
  • Provides structured outputs (transcripts, summaries, outcomes) for easy integration

Cons

  • Requires a telephony backend and consent management, adding setup complexity
  • Limited to outbound calls; no inbound or real-time streaming mentioned
  • Dependency on external call infrastructure may affect reliability

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Enables direct voice communication from AI agents without custom telephony code
  • Emphasizes consent, aligning with responsible calling practices
  • Provides structured outputs (transcripts, summaries, outcomes) for easy integration

Cons

  • Requires a telephony backend and consent management, adding setup complexity
  • Limited to outbound calls; no inbound or real-time streaming mentioned
  • Dependency on external call infrastructure may affect reliability
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