standard-vocal-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| VAPI_TOKEN | Yes | Your Vapi API token | |
| OPENAI_API_KEY | Yes | Your OpenAI API key, used by run_eval to simulate scenarios | |
| STANDARD_VOCAL_STATE_DIR | No | Directory where prompt snapshots are stored. Overrides the default .standard-vocal/ directory |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| list_agentsA | List the Vapi assistants on this account: name, id, model, voice, transcriber, creation date. Start here to find the assistantId for run_eval / prompt_diff / regression_gate. |
| deploy_agentA | Deploy a full production phone agent for a market (fr, us, sv) and a vertical (elagueur, plombier, tree-service, plumber, jardineria, plomeria). Creates the Vapi assistant with prompt, voice, transcriber and keywords baked in. One call = one working agent. |
| run_evalB | The agent tests itself. Simulates N scripted scenarios via the LLM (no audio cost), scores behavior (close speed, no price, spelled confirmation, urgency handling), returns a /100 report with PASS/WARN/FAIL. |
| audio_forensicsA | Download the 3 recording tracks of a call (mono/customer/assistant), run RMS analysis, and locate the noise source. Automates the manual audio investigation. |
| prompt_diffA | Version and diff assistant prompts. snapshot = capture current prompt from Vapi into local history. diff = compare two versions. rollback = push an old prompt back. |
| regression_gateA | CI for prompts. Runs run_eval against the current assistant and blocks the update if the score regressed vs the stored baseline. Returns allow/deny. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 6 tools
Each tool targets a distinct responsibility: listing, deploying, evaluating, analyzing audio, diffing prompts, and gating regressions. Even run_eval and regression_gate are clearly separated, with the former generating scores and the latter comparing against a baseline.
The first three tools follow a verb_noun pattern (list_agents, deploy_agent, run_eval), while the last three are noun-centric (audio_forensics, prompt_diff, regression_gate). This split in grammatical structure makes the naming convention inconsistent and harder to predict.
Six tools is well-scoped for a specialized server focused on voice agent lifecycle and evaluation. Every tool earns its place, and the count is neither too small nor bloated.
The set covers the core workflow: discover agents, deploy new ones, run tests, analyze call audio, version prompts, and gate updates. Minor gaps include no delete_agent or direct update_agent, but these are not critical for the server's apparent purpose.