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SDK regeneration
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‎.fern/metadata.json‎

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{
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"cliVersion": "0.107.3",
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"generatorName": "fernapi/fern-python-sdk",
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"generatorVersion": "4.36.2",
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"generatorConfig": {
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"timeout_in_seconds": 240,
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"default_bytes_stream_chunk_size": 1024,
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"inline_request_params": false,
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"follow_redirects_by_default": true,
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"recursion_limit": 5000,
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"pydantic_config": {
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"skip_validation": true
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},
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"client": {
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"class_name": "BaseElevenLabs",
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"filename": "base_client.py",
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"exported_class_name": "ElevenLabs",
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"exported_filename": "client.py"
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},
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"extra_dependencies": {
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"requests": ">=2.20",
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"websockets": ">=11.0",
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"pyaudio": {
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"version": ">=0.2.14",
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"optional": true
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}
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},
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"extra_dev_dependencies": {
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"types-pyaudio": "^0.2.16.20240516"
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},
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"extras": {
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"pyaudio": [
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"pyaudio"
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]
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},
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"additional_init_exports": [
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{
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"from": "play",
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"imports": [
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"play",
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"save",
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"stream"
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]
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},
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{
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"from": "realtime",
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"imports": [
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"RealtimeEvents",
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"RealtimeAudioOptions",
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"RealtimeUrlOptions",
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"AudioFormat",
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"CommitStrategy",
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"RealtimeConnection"
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]
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}
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]
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}
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}

‎poetry.lock‎

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‎pyproject.toml‎

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@@ -3,7 +3,7 @@ name = "elevenlabs"
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[tool.poetry]
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name = "elevenlabs"
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version = "v2.22.1"
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version = "v2.23.0"
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description = ""
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readme = "README.md"
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authors = []
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{ include = "elevenlabs", from = "src"}
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]
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[project.urls]
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[tool.poetry.urls]
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Repository = 'https://github.com/elevenlabs/elevenlabs-python'
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[tool.poetry.dependencies]

‎reference.md‎

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@@ -7009,6 +7009,8 @@ client.conversational_ai.conversations.list(
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call_successful="success",
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call_start_before_unix=1,
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call_start_after_unix=1,
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call_duration_min_secs=1,
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call_duration_max_secs=1,
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user_id="user_id",
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page_size=1,
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summary_mode="exclude",
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<dl>
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<dd>
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**call_duration_min_secs:** `typing.Optional[int]` — Minimum call duration in seconds.
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</dd>
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</dl>
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<dl>
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<dd>
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**call_duration_max_secs:** `typing.Optional[int]` — Maximum call duration in seconds.
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</dd>
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</dl>
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<dl>
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<dd>
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**user_id:** `typing.Optional[str]` — Filter conversations by the user ID who initiated them.
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</dd>
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<dl>
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<dd>
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**evaluation_params:** `typing.Optional[typing.Union[str, typing.Sequence[str]]]` — Evaluation filters. Repeat param. Format: criteria_id:result. Example: eval=value_framing:success
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</dd>
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</dl>
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<dl>
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<dd>
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**data_collection_params:** `typing.Optional[typing.Union[str, typing.Sequence[str]]]` — Data collection filters. Repeat param. Format: id:op:value where op is one of eq|neq|gt|gte|lt|lte|in|exists|missing. For in, pipe-delimit values.
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</dd>
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</dl>
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<dl>
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<dd>
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**tool_names:** `typing.Optional[typing.Union[str, typing.Sequence[str]]]` — Filter conversations by tool names used during the call.
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</dd>
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</dl>
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<dl>
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<dd>
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**page_size:** `typing.Optional[int]` — How many conversations to return at maximum. Can not exceed 100, defaults to 30.
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</dd>
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<dl>
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<dd>
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**branch_id:** `typing.Optional[str]` — ID of the branch to run the tests on. If not provided, the tests will be run on the agent default configuration.
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</dd>
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</dl>
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<dl>
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<dd>
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**request_options:** `typing.Optional[RequestOptions]` — Request-specific configuration.
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</dd>
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```python
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from elevenlabs import (
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ElevenLabs,
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LiteralJsonSchemaProperty,
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ObjectJsonSchemaPropertyInput,
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QueryParamsJsonSchema,
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ToolRequestModel,
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ToolRequestModelToolConfig_ApiIntegrationWebhook,
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WebhookToolApiSchemaConfigInput,
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)
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client = ElevenLabs(
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description="description",
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api_integration_connection_id="api_integration_connection_id",
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base_api_schema=WebhookToolApiSchemaConfigInput(
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url="https://example.com/agents/{agent_id}",
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method="GET",
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path_params_schema={
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"agent_id": LiteralJsonSchemaProperty(
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type="string",
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)
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},
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query_params_schema=QueryParamsJsonSchema(
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properties={
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"key": LiteralJsonSchemaProperty(
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type="string",
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description="My property",
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is_system_provided=False,
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dynamic_variable="",
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constant_value="",
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)
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},
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),
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request_body_schema=ObjectJsonSchemaPropertyInput(),
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request_headers={"Authorization": "Bearer {api_key}"},
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),
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),
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),
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)
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```python
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LiteralJsonSchemaProperty,
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ObjectJsonSchemaPropertyInput,
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QueryParamsJsonSchema,
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WebhookToolApiSchemaConfigInput,
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client = ElevenLabs(
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base_api_schema=WebhookToolApiSchemaConfigInput(
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url="https://example.com/agents/{agent_id}",
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method="GET",
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path_params_schema={
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"agent_id": LiteralJsonSchemaProperty(
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type="string",
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)
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},
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query_params_schema=QueryParamsJsonSchema(
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properties={
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"key": LiteralJsonSchemaProperty(
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type="string",
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description="My property",
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is_system_provided=False,
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dynamic_variable="",
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constant_value="",
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)
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},
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),
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request_body_schema=ObjectJsonSchemaPropertyInput(),
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request_headers={"Authorization": "Bearer {api_key}"},
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),
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)
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</dl>
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</dd>
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</dl>
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</details>
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<details><summary><code>client.conversational_ai.mcp_servers.<a href="src/elevenlabs/conversational_ai/mcp_servers/client.py">delete</a>(...)</code></summary>
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<dl>
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<dd>
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#### 📝 Description
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<dd>
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<dl>
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<dd>
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Delete a specific MCP server configuration from the workspace.
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</dd>
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</dl>
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</dd>
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</dl>
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#### 🔌 Usage
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<dl>
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<dd>
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<dl>
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<dd>
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```python
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client = ElevenLabs(
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api_key="YOUR_API_KEY",
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)
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client.conversational_ai.mcp_servers.delete(
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mcp_server_id="mcp_server_id",
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)
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```
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</dd>
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</dl>
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</dd>
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</dl>
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#### ⚙️ Parameters
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<dl>
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<dd>
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<dl>
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<dd>
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**mcp_server_id:** `str` — ID of the MCP Server.
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</dd>
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</dl>
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<dl>
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<dd>
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**request_options:** `typing.Optional[RequestOptions]` — Request-specific configuration.
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</dd>
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</dl>
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</dd>
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</dl>
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**feedback:** `UserFeedbackScore` — Either 'like' or 'dislike' to indicate the feedback for the conversation.
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**feedback:** `typing.Optional[UserFeedbackScore]` — Either 'like' or 'dislike' to indicate the feedback for the conversation.
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**input_schema:** `typing.Optional[typing.Dict[str, typing.Optional[typing.Any]]]` — The input schema of the MCP tool (the schema defined on the MCP server before ElevenLabs does any extra processing)
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**input_schema:** `typing.Optional[typing.Dict[str, typing.Any]]` — The input schema of the MCP tool (the schema defined on the MCP server before ElevenLabs does any extra processing)
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**branch_id:** `typing.Optional[str]` — ID of the branch to run the tests on. If not provided, the tests will be run on the agent default configuration.
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</dd>
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</dl>
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**request_options:** `typing.Optional[RequestOptions]` — Request-specific configuration.
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</dd>

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