Vapi MCP Server
OfficialManage Vapi voice assistants, outbound calls, phone numbers, tools, and simulation testing from any MCP-capable agent.
Assistants: list, get, create, and update assistants (names, LLM, voice, transcriber, first message, instructions)
Calls: list call history, get call details, and start outbound calls immediately or scheduled, with dynamic variables via
assistantOverrides.variableValuesPhone numbers: list and inspect phone numbers
Tools (function calling): list, get, create, and update custom tools —
function,apiRequest,transferCall, andsmstypesSimulations: build and run test suites — create personalities, scenarios with evaluations, simulations, and suites; run them against an assistant or squad; inspect runs and full run items with transcripts
Docs lookup:
ask_vapi_docsreturns current Vapi documentation passages and source URLsSkills: search public VapiAI skills and load
SKILL.mdor supporting files with reusable instructionsSchema reference:
get_api_schemalooks up OpenAPI schema names to discover fields accepted viaadditionalFields
Allows the MCP server to be installed and run via NPX, making it easy to integrate Vapi's capabilities through the NPM package ecosystem.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Vapi MCP Server call my appointment reminder assistant to schedule a follow-up for next week"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Vapi MCP Server
Build AI voice assistants and phone agents with Vapi from any agent or app that speaks the Model Context Protocol.
Connect to the hosted server
You don't need to clone, install or run anything. Vapi hosts this server for you:
URL:
https://mcp.vapi.ai/mcp(Streamable HTTP)Header:
Authorization: Bearer YOUR_VAPI_API_KEY
Get an API key from the Vapi dashboard.
👉 Step-by-step setup for Codex, Claude Code, Cursor, VS Code, Hermes and Claude Desktop
The two most common setups:
Claude Code
export VAPI_API_KEY="YOUR_VAPI_API_KEY"
claude mcp add --transport http --scope user vapi \
https://mcp.vapi.ai/mcp \
--header 'Authorization: Bearer ${VAPI_API_KEY}'Codex
export VAPI_API_KEY="YOUR_VAPI_API_KEY"
codex mcp add vapi --url https://mcp.vapi.ai/mcp \
--bearer-token-env-var VAPI_API_KEYKeep VAPI_API_KEY set whenever you launch your agent. Start a new session, then try:
List my Vapi assistants.I want to build a voice assistant that can schedule appointments.Call +1234567890 using my appointment reminder assistant with these details:
- Customer name: Sarah Johnson
- Appointment date: March 25th
- Appointment time: 2:30 PMSchedule a call with my support assistant for next Tuesday at 3:00 PM to +1555123456The legacy SSE endpoint (
https://mcp.vapi.ai/sse) is deprecated. Move existing remote configurations tohttps://mcp.vapi.ai/mcp.
Optional: add the Vapi agent skill
The skill directory contains reusable instructions for AI coding agents that support Agent Skills. Install it using your host's skill installation process.
For Claude Code:
mkdir -p ~/.claude/skills/vapi
curl -o ~/.claude/skills/vapi/SKILL.md https://raw.githubusercontent.com/VapiAI/mcp-server/main/skill/SKILL.mdUsing Variable Values in Assistant Prompts
The create_call action supports passing dynamic variables through assistantOverrides.variableValues. Use double curly braces in your assistant's prompts: {{variableName}}.
Example Prompt with Variables
Hello {{customerName}}, this is a reminder about your appointment on {{appointmentDate}} at {{appointmentTime}} with {{doctorName}}.Default Variables
These are automatically available (no need to pass):
{{now}}- Current date and time (UTC){{date}}- Current date (UTC){{time}}- Current time (UTC){{month}}- Current month (UTC){{day}}- Current day of month (UTC){{year}}- Current year (UTC){{customer.number}}- Customer's phone number
See Vapi documentation for advanced date/time formatting.
Related MCP server: Lark MCP Server
Oh, you're still here?
You must want to leave feedback, run a local server yourself or peek under the hood. Read on.
Leave feedback
Found a bug or want a tool we don't have? Open an issue.
Have a question or want to talk it through? Join the Vapi Discord.
Want to fix it yourself? Pull requests are welcome. See Development for how to build and test.
Run a local server
Run the server on your own machine if your client only supports local stdio servers or you want to try unreleased changes. It uses the same tools as the hosted server.
Configure your MCP client to run:
npx -y @vapi-ai/mcp-serverSet VAPI_TOKEN to your Vapi API key in the server environment. MCP client configuration formats vary, but the server definition generally looks like this:
{
"mcpServers": {
"vapi": {
"command": "npx",
"args": ["-y", "@vapi-ai/mcp-server"],
"env": {
"VAPI_TOKEN": "<your_vapi_token>"
}
}
}
}For Claude Code:
claude mcp add -e VAPI_TOKEN=your_vapi_token vapi -- npx -y @vapi-ai/mcp-serverFor Claude Desktop, add the configuration above to the Claude Desktop configuration file.
To run a build from this repository instead, see Local Development Config.
Peek under the hood
Available Tools
Documentation
Tool | Description |
| Query the Fern docs MCP for current documentation passages and source URLs |
ask_vapi_docs({"question":"How do assistant hooks work?","topK":8}) forwards to
searchDocs at https://docs.vapi.ai/_mcp/server. The result preserves Fern's
content, source links and error flag. This endpoint currently returns passages
for the calling agent to synthesize, rather than a generated answer. topK
defaults to 8 (maximum 20). Each request owns its MCP connection, supports caller
cancellation, times out after 30 seconds and closes the connection afterwards.
This tool needs outbound HTTPS to the Fern endpoint. It makes no Vapi API calls
and sends no Vapi credentials upstream. The server still requires VAPI_TOKEN
at startup. Discovery through tools/list makes no network requests; upstream
failures are returned as tool errors. No extra MCP connection is needed. Do not
include secrets or private customer data in docs questions.
Assistants
Tool | Description |
| List assistants in pages of up to 10 |
| Get assistant by ID |
| Create new assistant |
| Update assistant |
Calls
Tool | Description |
| List call history in pages of up to 10 |
| Get call details |
| Start outbound call (immediate or scheduled) |
Phone Numbers
Tool | Description |
| List phone numbers in pages of up to 10 |
| Get phone number details |
Tools (Function Calling)
Tool | Description |
| List custom tools in pages of up to 10 |
| Get tool details |
| Create tool for API integration |
| Update tool |
Public Skills
Tool | Description |
| Search public Vapi skills by keywords; omit |
| Read a skill's |
For example, call search_skills({"query":"simulations"}), then
load_skill({"name":"simulations"}). The load result includes a files list;
read a supporting file with load_skill({"name":"simulations","path":"references/example.md"}),
using an exact path from that list. Loading returns instructions for the current
task; it does not install skills or run scripts.
Skills come directly from the public VapiAI/skills
repository, including experimental skills. Discovery uses its GitHub tree rather
than the proposed skills manifest. Each server caches a commit-pinned snapshot
for five minutes, so file reads within that snapshot use the same revision. Search
matches names, descriptions and instruction text; it returns at most limit
results (default 10, maximum 30) and the total match count. load_skill returns
one text file at a time, up to 512 KB, with its source URL and revision.
The skills tools need outbound HTTPS to public GitHub. They make no Vapi API
calls and send no Vapi credentials upstream. The server still requires
VAPI_TOKEN at startup. Discovery through tools/list makes no network requests;
upstream failures are returned as tool errors. No GitHub token is needed for this
public content. GitHub's unauthenticated API rate limits apply.
Simulations
Tool | Description |
| List simulated callers |
| Create a simulated caller with a tester assistant |
| List tester scripts and evaluations |
| Create a tester script and evaluations |
| List scenario/personality pairs |
| Pair a scenario with a personality |
| List groups of simulations |
| Group simulations into a suite |
| Run simulations or suites against an assistant or squad |
| List runs and filter by status or target |
| Get run status and item summaries |
| Get a full item including transcript and results |
The catalog contains 29 tools. Simulation lists default to 50 results.
get_simulation_run returns the first 100 item summaries, with API pagination
metadata in itemsMetadata and itemsTruncated: true when more items exist.
Legacy array responses are also supported. Use get_simulation_run_item for
the full details of a known item.
Development
# Install dependencies
npm install
# Build
npm run build
# Test with MCP inspector
npm run inspectorLocal Development Config
{
"mcpServers": {
"vapi-local": {
"command": "node",
"args": ["<path>/dist/index.js"],
"env": {
"VAPI_TOKEN": "<your_vapi_token>"
}
}
}
}Testing
# Safe default suite (build, mocked execution, contract, and stdio compatibility)
npm test
# Unit tests (mocked public tool execution and catalog contract)
npm run test:unit
# Documentation/tool-catalog consistency lint
npm run test:docs
# Full TypeScript check (production and test code)
npm run typecheck
# Build and run local stdio protocol compatibility tests (no Vapi API calls)
npm run test:stdio
# Pack, install, and launch the package from a clean temporary consumer
npm run test:package
# Live read-only API tests
export VAPI_TOKEN=your_token_here
npm run test:live:readonly
# Live mutating tests (creates and cleans up disposable assistants and tools)
export VAPI_TOKEN=your_test_org_token_here
npm run test:live:mutatingInput validation from OpenAPI
All 21 parameterized MCP tools use imported OpenAPI constraints through
Zod's experimental z.fromJSONSchema(), pinned to Zod 4.6.7. This covers
assistant names/LLMs/voices/transcribers, call schedules and customer numbers,
lookup/update IDs, function parameters, transfer destinations, HTTP methods,
timeouts and retry plans, plus all 12 simulation tools. The four original list
tools have local empty input schemas.
src/schemas/assistant-openapi.json is the compact projection for the original
tool surfaces (the filename is retained from the initial assistant cutover). It
records the public API spec source SHA-256 and
includes the recursive JSON-schema definitions needed for function parameters
and request bodies. Builds and installs use it without network access. Refresh
explicitly with npm run schemas:snapshot, or pass a saved spec with
npm run schemas:snapshot -- /path/spec.json.
src/schemas/simulation-openapi.json bundles the full simulation DTOs and their
referenced definitions from the same public spec. The same refresh command
updates both snapshots. Simulation validation includes names, folder paths,
UUIDs, instructions, evaluations, nested tester assistants and structured
outputs. Scenario/suite additionalFields are validated after merging, so they
cannot override an API constraint. Large nested assistant and structured-output
objects have compact advertised envelopes; their full API contracts are checked
at runtime. The shared summary projection omits long documentation and recursive
definitions from simulation discovery. The 25-tool catalog is about 28 KB.
No runtime schema fetch or
get_api_schema tool is required.
Simulation aliases remain local adapters: run_simulations takes exactly one
assistant/squad target and at least one simulation/suite ID, then builds the API
request. Integer iterations and integer page sizes of 1–100 are MCP policies;
API iteration bounds and parameter formats come from the snapshot. The item
lookup endpoint publishes plain strings for its IDs, so those are not assigned
UUID constraints from a different endpoint.
The shared normalizer also represents empty preset enums as always-failing
branches and preserves property names such as oneOf and default when walking
JSON Schema definitions.
When upgrading @vapi-ai/server-sdk, refresh and review the bundled schema in
the same PR, then run npm run typecheck, npm test, and npm run test:package.
Check changes against the SDK's request types and the MCP adapters below. The
public endpoint serves the current API spec, not a spec version tied to the SDK
release, so refreshing does not by itself guarantee compatibility. Keep the
reviewed schema bundled with the release; do not refresh it during installation
or startup.
The adapter documents published contract corrections: overlapping enum/string
oneOf alternatives become anyOf; duplicate enum values and JavaScript regex
delimiters are removed; the contradictory object/string-enum annotation on
BackoffPlan.type is corrected. Provider variants reject undeclared fields.
Spec defaults do not inject request fields; MCP defaults remain separate.
For the original compact assistant tools, variants requiring fields outside
the current interface remain excluded: custom
voice, Neuphonic voice, custom transcriber, Speechmatics transcriber, and custom
LLM. Adding their required fields needs an explicit interface extension.
MCP wrappers preserve field aliases and sparse updates. URL checks and string-valued header maps remain explicit transport rules because the spec only describes a string/object. API-request header maps and SMS metadata retain legacy MCP representations; they are explicit compatibility adapters, not claimed to be full API DTO validation. SMS metadata is not described in the published DTO. Response summaries also remain local: they are transformed MCP representations, not raw API DTOs.
Validation failures return isError: true, concise text and structured
validationError details: tool name, issue code, field path, message and allowed
choices where relevant. Errors select the supplied provider's union branch,
include at most 12 issues and 8 allowed choices per issue, and indicate
truncation. Submitted values and credential contents are not echoed. Agents
should correct the listed fields and retry; a validation failure never invokes
the API handler. Tests exercise this correction loop through a real MCP client.
tools/list advertises a compact input summary derived from the same validators:
field names, basic types, required fields, defaults, and short constraints. It
omits provider/model catalogs, lengthy API documentation, and recursive schema
definitions. The full OpenAPI-derived validator still runs before any API call;
the advertised summary is intentionally broader. Catalog tests cap the
original 13-tool list at 20 KB, the 12 simulation tools at 10 KB, and the complete
25-tool list at 30 KB to prevent unexpected agent-context growth.
npm test includes schema contract tests, independent Ajv parity cases, and
validation-feedback tests. The existing live compatibility
suites cover read-only resources and disposable assistants/custom tools.
References
Available Tools
29 toolsask_vapi_docsARead-only
Ask about current Vapi documentation through the Fern docs MCP. Returns relevant documentation passages and source URLs; use them to answer the question.
Inputs: question (required), topK.
create_assistantC
Creates a new Vapi assistant
Inputs: name (required), llm, voice, toolIds, +4 more.
create_callC
Creates a outbound call
Inputs: customer, assistantId, scheduledAt, phoneNumberId, +1 more.
create_simulationB
Creates a simulation that pairs a scenario with a personality. Run it with run_simulations.
Inputs: scenarioId (required), personalityId (required), name, path.
create_simulation_personalityC
Creates a simulation personality: the simulated caller that talks to the assistant under test
Inputs: name (required), assistant (required), path.
create_simulation_scenarioC
Creates a simulation scenario: instructions for the tester plus evaluations that decide whether the assistant passed
Inputs: name (required), evaluations (required), instructions (required), path, +1 more.
create_simulation_suiteB
Creates a simulation suite that groups simulations so they can be run together
Inputs: name (required), simulationIds (required), path, additionalFields.
create_toolC
Creates a new Vapi tool
Inputs: type (required), sms, name, function, +4 more.
get_api_schemaA
Looks up a schema in the Vapi API reference (the OpenAPI spec the Vapi SDKs are generated from). Pass search to find schema names, then name to get one schema. References to other schemas are left as "#/components/schemas/" and listed in referencedSchemas, so look those up next if you need them. Use it to find fields that other tools accept through additionalFields.
Inputs: name, search.
get_assistantB
Gets a Vapi assistant by ID
Inputs: assistantId (required).
get_callC
Gets details of a specific call
Inputs: callId (required).
get_phone_numberB
Gets details of a specific phone number
Inputs: phoneNumberId (required).
get_simulation_runA
Gets a simulation run with its status, item counts, and the first 100 item summaries. itemsTruncated indicates omitted items; itemsMetadata preserves API pagination metadata. Use get_simulation_run_item for an item’s transcript and call details.
Inputs: runId (required).
get_simulation_run_itemB
Gets one simulation run item in full, including results, call snapshots, transcript, and improvement suggestions
Inputs: runId (required), itemId (required).
get_toolC
Gets details of a specific tool
Inputs: toolId (required).
list_assistantsB
Lists all Vapi assistants
Inputs: no named parameters.
list_callsC
Lists all Vapi calls
Inputs: no named parameters.
list_phone_numbersB
Lists all Vapi phone numbers
Inputs: no named parameters.
list_simulation_personalitiesA
Lists simulation personalities: the simulated callers (testers) used in Vapi simulations
Inputs: limit.
list_simulation_runsC
Lists simulation runs, newest first
Inputs: limit, status, targetId.
list_simulationsB
Lists simulations. Each simulation pairs one scenario with one personality.
Inputs: limit.
list_simulation_scenariosC
Lists simulation scenarios: the scripts testers follow and the checks that decide pass or fail
Inputs: name, limit.
list_simulation_suitesC
Lists simulation suites: named groups of simulations
Inputs: limit.
list_toolsB
Lists all Vapi tools
Inputs: no named parameters.
load_skillARead-only
Read a public Vapi skill or one of its supporting files. Start with SKILL.md, then load relevant files from the returned file list as needed. Returns instructions for this task; does not install skills or execute scripts.
Inputs: name (required), path.
run_simulationsA
Starts a simulation run of simulations and/or suites against an assistant or squad. Returns the run with its ID and a dashboard URL to share with the user. Check progress with get_simulation_run.
Inputs: squadId, suiteIds, transport, iterations, +3 more.
search_skillsARead-only
Find Vapi agent skills in the public VapiAI/skills repository by name, description or content. Omit query to browse. Use load_skill to read a result.
Inputs: limit, query.
update_assistantC
Updates an existing Vapi assistant
Inputs: assistantId (required), llm, name, voice, +5 more.
update_toolC
Updates an existing Vapi tool
Inputs: toolId (required), sms, name, function, +4 more.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
TDQS
Scored across 29 tools
Most tools target a distinct resource+action pair, and the simulation cluster (personality vs scenario vs simulation vs suite vs run) is disambiguated by explicit descriptions. The closest overlaps are list_simulations vs list_simulation_runs and the four read/query helpers (ask_vapi_docs, get_api_schema, search_skills, load_skill), which are related but still separable.
Nearly everything follows a snake_case verb_noun pattern (list_assistants, create_call, get_simulation_run_item), which is predictable. Minor deviations exist in the docs/skills group where 'ask_vapi_docs' and 'load_skill' depart slightly from the get_/list_/create_ convention.
29 tools is heavy and well past the comfortable range, dominated by 12 near-repetitive simulation tools (list/create/get for personalities, scenarios, simulations, suites, runs). While they map to real product areas, the surface feels bloated rather than deliberately scoped.
Core flows (create assistant/call/tool, run simulations and inspect results) are covered, but lifecycle coverage is patchy: no delete operations anywhere, phone numbers are read-only (list/get only, no create/update/delete), and simulations have list/create but no get_simulation or update/delete.
Maintenance
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