Use when writing or reviewing Python code in this repo that calls Deepgram Management APIs - projects, API keys, members, invites, usage, billing, models, and reusable Voice Agent configurations. Covers `client.manage.v1.projects`, project-scoped resources under `client.manage.v1.projects.*` (keys, members, members.invites, usage, billing, models, requests), global `client.manage.v1.models`, think-model discovery at `client.agent.v1.settings.think.models`, and `client.voice_agent.configurations.*`. Use `deepgram-python-voice-agent` when you want to run an agent interactively, this skill to PERSIST/LIST agent configs. Triggers include "management API", "list projects", "API keys", "members", "usage stats", "billing", "list models", "agent configurations", "manage.v1".
npx skills add https://github.com/deepgram/deepgram-python-sdk --skill deepgram-python-management-api
Administrative REST endpoints at api.deepgram.com/v1/projects, /v1/models, and reusable agent configuration storage. Project-scoped resources live under client.manage.v1.projects.* (keys, members, members.invites, usage, billing, models, requests). Global models at client.manage.v1.models. Think-model discovery at client.agent.v1.settings.think.models. Reusable agent configs at client.voice_agent.configurations.*.
client.manage.v1.models.list() returns the active STT/TTS set.agent block of a Settings message on the server, reference by agent_id. The stored blob is the agent object only (listen / think / speak providers + prompt), not the full AgentV1Settings.Use a different skill when:
deepgram-python-voice-agent.from dotenv import load_dotenv
load_dotenv()
from deepgram import DeepgramClient
client = DeepgramClient()
Header: Authorization: Token <api_key>. All methods are REST.
# Projects
projects = client.manage.v1.projects.list()
for p in projects.projects:
print(p.project_id, p.name)
project = client.manage.v1.projects.get(project_id=projects.projects[0].project_id)
client.manage.v1.projects.update(project_id=project.project_id, name="New name")
# client.manage.v1.projects.delete(project_id=...) # irreversible
# client.manage.v1.projects.leave(project_id=...)
# Models
models = client.manage.v1.models.list()
print("STT:", [m.canonical_name for m in models.stt])
print("TTS:", [m.canonical_name for m in models.tts])
# Include deprecated/outdated models
older = client.manage.v1.models.list(include_outdated=True)
# Per-project model access
project_models = client.manage.v1.projects.models.list(project_id=project.project_id)
All project-scoped resources live under client.manage.v1.projects.*:
# Keys — `create` takes a single `request=` payload, not top-level kwargs
keys = client.manage.v1.projects.keys.list(project_id=pid)
client.manage.v1.projects.keys.create(
project_id=pid,
request={"comment": "CI key", "scopes": ["usage:write"]},
)
client.manage.v1.projects.keys.delete(project_id=pid, key_id=kid)
# Members + invites (invites are nested under members; method is `create`, not `send`)
members = client.manage.v1.projects.members.list(project_id=pid)
invites = client.manage.v1.projects.members.invites.list(project_id=pid)
client.manage.v1.projects.members.invites.create(project_id=pid, email="[email protected]", scope="member")
# Usage (get, not list) + billing balances (nested)
usage = client.manage.v1.projects.usage.get(project_id=pid)
usage_breakdown = client.manage.v1.projects.usage.breakdown.list(project_id=pid)
balance = client.manage.v1.projects.billing.balances.get(project_id=pid)
See examples/51-55 for each sub-module.
# List reusable configs
configs = client.voice_agent.configurations.list(project_id=pid)
# Create: `config` is a JSON string of the `agent` BLOCK ONLY — not the full
# Settings message. Do NOT include top-level Settings fields like `audio`;
# those are sent at connect-time in the live Settings message. The stored
# `agent_id` later replaces the inline `agent` object in a Settings message.
import json
config_json = json.dumps({
"listen": {"provider": {"type": "deepgram", "model": "nova-3"}},
"think": {"provider": {"type": "open_ai", "model": "gpt-4o-mini"}, "prompt": "..."},
"speak": {"provider": {"type": "deepgram", "model": "aura-2-asteria-en"}},
})
created = client.voice_agent.configurations.create(
project_id=pid,
config=config_json,
metadata={"label": "support-en"},
)
print(created.agent_id)
# Update metadata (immutable config body — create a new one to change behavior)
client.voice_agent.configurations.update(project_id=pid, agent_id=created.agent_id, metadata={"label": "v2"})
# Get / delete
one = client.voice_agent.configurations.get(project_id=pid, agent_id=created.agent_id)
# client.voice_agent.configurations.delete(project_id=pid, agent_id=...)
Think-provider model discovery (which LLMs Agent supports):
think_models = client.agent.v1.settings.think.models.list()
from deepgram import AsyncDeepgramClient
client = AsyncDeepgramClient()
projects = await client.manage.v1.projects.list()
reference.md — "Manage V1 Projects/Keys/Members/Invites/Usage/Billing/Models", "Voice Agent Configurations"./llmstxt/developers_deepgram_llms_txt.Token auth, not Bearer..projects.*. There is no top-level client.manage.v1.keys / .members / .invites / .usage / .billing. Use client.manage.v1.projects.keys, ...projects.members, ...projects.members.invites, ...projects.usage, ...projects.billing.balances, and ...projects.requests for request logs. The only top-level client.manage.v1.* namespaces are projects and models.client.agent.v1.settings.think.models.list(). There is no client.manage.v1.agent.*.config=json.dumps(...).agent block only, not the full Settings message. Do not include top-level fields like audio — those go in the live Settings message at connect time.include_outdated=True on models.list() when pinning older models.client.manage.v1.models.list() returns all; client.manage.v1.projects.models.list(project_id=...) returns what the project can access.10. Returned agent configs are uninterpolated — raw stored JSON string. Parse before use.
examples/50-management-projects.pyexamples/51-management-keys.pyexamples/52-management-members.pyexamples/53-management-invites.pyexamples/54-management-usage.pyexamples/55-management-billing.pyexamples/56-management-models.pytests/wire/test_manage_v1_projects.pytests/wire/test_manage_v1_models.pytests/wire/test_voiceAgent_configurations.pydeepgram-python-voice-agent — run an agent (use a config created here)For cross-language Deepgram product knowledge — the consolidated API reference, documentation finder, focused runnable recipes, third-party integration examples, and MCP setup — install the central skills:
npx skills add deepgram/skills
This SDK ships language-idiomatic code skills; deepgram/skills ships cross-language product knowledge (see api, docs, recipes, examples, starters, setup-mcp).
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
Automatically creates user-facing changelogs from git commits by analyzing commit history, categorizing changes, and transforming technical commits into clear, customer-friendly release notes. Turns hours of manual changelog writing into minutes of automated generation.
Use when implementation is complete, all tests pass, and you need to decide how to integrate the work - guides completion of development work by presenting structured options for merge, PR, or cleanup
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
React Native and Expo best practices for building performant mobile apps. Use when building React Native components, optimizing list performance, implementing animations, or working with native modules. Triggers on tasks involving React Native, Expo, mobile performance, or native platform APIs.
React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.
Next.js best practices - file conventions, RSC boundaries, data patterns, async APIs, metadata, error handling, route handlers, image/font optimization, bundling
Use when starting feature work that needs isolation from current workspace or before executing implementation plans - creates isolated git worktrees with smart directory selection and safety verification
Take deepgram/deepgram-python-management-api from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.
The instructions reference npx.
Without those the skill loads but fails at the first command.