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API reference / YouTube / Activities list

Activities list

Read-only YouTube Data API v3 activities list endpoint.

1 credit per successful call Errors are never charged

Request

GET https://socialgraph.dev/api/v1/youtube/activities

Send your API key as Authorization: Bearer YOUR_API_KEY. Parameters go in the query string.

Parameters

NameTypeDescription
part
required
string Required. Use id, snippet or contentDetails.
channelId
required
string Required. Return activities for this channel. For example: UC_x5XG1OV2P6uZZ5FSM9Ttw
maxResults
optional
integer Maximum results per page (0–50).
pageToken
optional
string Token from a previous response.
publishedAfter
optional
string RFC 3339 lower bound for publish time. (YYYY-MM-DDThh:mm:ss.sZ)
publishedBefore
optional
string RFC 3339 upper bound for publish time. (YYYY-MM-DDThh:mm:ss.sZ)
regionCode
optional
string ISO 3166-1 alpha-2 region code. For example: US

Code examples


Example response

{
    "etag": "6_jFitH_2QIynYzI612FtWGfxJQ",
    "kind": "youtube#activityListResponse",
    "items": [
        {
            "id": "MTUxNzkxOTE4MDExMTc5MTkxODAxMTAwMDYyNA",
            "etag": "OQ8UkdAJS--_XHJuq0NpMXCM2aI",
            "kind": "youtube#activity",
            "snippet": {
                "type": "upload",
                "title": "Gemini 4 Argon and Google Antigravity: From 2D concept to 3D cathedral",
                "channelId": "UC_x5XG1OV2P6uZZ5FSM9Ttw",
                "thumbnails": {
                    "fhd": {
                        "url": "https://i.ytimg.com/vi/OYp5j2RihPE/fhddefault.jpg",
                        "width": 1920,
                        "height": 1080
                    },
                    "high": {
                        "url": "https://i.ytimg.com/vi/OYp5j2RihPE/hqdefault.jpg",
                        "width": 480,
                        "height": 360
                    },
                    "maxres": {
                        "url": "https://i.ytimg.com/vi/OYp5j2RihPE/maxresdefault.jpg",
                        "width": 1280,
                        "height": 720
                    },
                    "medium": {
                        "url": "https://i.ytimg.com/vi/OYp5j2RihPE/mqdefault.jpg",
                        "width": 320,
                        "height": 180
                    },
                    "default": {
                        "url": "https://i.ytimg.com/vi/OYp5j2RihPE/default.jpg",
                        "width": 120,
                        "height": 90
                    },
                    "standard": {
                        "url": "https://i.ytimg.com/vi/OYp5j2RihPE/sddefault.jpg",
                        "width": 640,
                        "height": 480
                    }
                },
                "description": "Watch how an autonomous AI agent takes a flat 2D concept image and reconstructs a photorealistic 3D cathedral in Blender from scratch. Tiago Aragona demonstrates how to connect Antigravity directly to Blender via the Model Context Protocol (MCP), leveraging Gemini 4 Argon across 45 iterative agentic loops to deduce complex architectural geometry, detail column fluting, and set up volumetric lighting.\n\n\n🔗Resources:\nGemini 4 Argon Blog → https://goo.gle/4zze7Rg\nAntigravity Website → https://goo.gle/4B3IxMW\n\n\n\nSubscribe to Google for Developers → https://goo.gle/developers    \n\n\n\nSpeakers: Tiago Aragona\nProducts Mentioned: Gemini 4 Argon, Antigravity, Blender, Model Context Protocol (MCP), Flow",
                "publishedAt": "2026-10-13T19:00:11+00:00",
                "channelTitle": "Google for Developers"
            }
        },
        {
            "id": "MTUxNzkxNTg2ODI0MTc5MTU4NjgyNDAwMDU1OA",
            "etag": "aHsUXDzVKAOeGtMlpl7DSMSKwKk",
            "kind": "youtube#activity",
            "snippet": {
                "type": "upload",
                "title": "Order in any language with Gemini 3.5 Live Translate",
                "channelId": "UC_x5XG1OV2P6uZZ5FSM9Ttw",
                "thumbnails": {
                    "high": {
                        "url": "https://i.ytimg.com/vi/IBVmenOroPs/hqdefault.jpg",
                        "width": 480,
                        "height": 360
                    },
                    "maxres": {
                        "url": "https://i.ytimg.com/vi/IBVmenOroPs/maxresdefault.jpg",
                        "width": 1280,
                        "height": 720
                    },
                    "medium": {
                        "url": "https://i.ytimg.com/vi/IBVmenOroPs/mqdefault.jpg",
                        "width": 320,
                        "height": 180
                    },
                    "default": {
                        "url": "https://i.ytimg.com/vi/IBVmenOroPs/default.jpg",
                        "width": 120,
                        "height": 90
                    },
                    "standard": {
                        "url": "https://i.ytimg.com/vi/IBVmenOroPs/sddefault.jpg",
                        "width": 640,
                        "height": 480
                    }
                },
                "description": "See how Gemini 3.5 Live Translate and Gemini 3.5 Transcribe work together to help an English speaker place a sushi order with a Japanese-speaking host, translating the conversation in real time.\n\nTry it now at Google AI Studio. Have questions? Drop them in the comments.\n\n\n🔗Resources:\nBlog  → https://goo.gle/4jbKjoM\nDeveloper documentation → https://goo.gle/3TPrgWR\n\n\nSubscribe to Google for Developers → https://goo.gle/developers    \n\n\n\nSpeakers: Sam Goldstein \nProducts Mentioned: Gemini",
                "publishedAt": "2026-10-09T23:00:24+00:00",
                "channelTitle": "Google for Developers"
            }
        },
        {
            "id": "MTUxNzkxNTcyNDM2MTc5MTU3MjQzNjAwMDg0Mg",
            "etag": "n5Dl_KHO6m8NUOYngLzqv39gvlg",
            "kind": "youtube#activity",
            "snippet": {
                "type": "upload",
                "title": "🤖 Operating real hardware with Gemini AI",
                "channelId": "UC_x5XG1OV2P6uZZ5FSM9Ttw",
                "thumbnails": {
                    "high": {
                        "url": "https://i.ytimg.com/vi/fMgcm9aXZyY/hqdefault.jpg",
                        "width": 480,
                        "height": 360
                    },
                    "maxres": {
                        "url": "https://i.ytimg.com/vi/fMgcm9aXZyY/maxresdefault.jpg",
                        "width": 1280,
                        "height": 720
                    },
                    "medium": {
                        "url": "https://i.ytimg.com/vi/fMgcm9aXZyY/mqdefault.jpg",
                        "width": 320,
                        "height": 180
                    },
                    "default": {
                        "url": "https://i.ytimg.com/vi/fMgcm9aXZyY/default.jpg",
                        "width": 120,
                        "height": 90
                    },
                    "standard": {
                        "url": "https://i.ytimg.com/vi/fMgcm9aXZyY/sddefault.jpg",
                        "width": 640,
                        "height": 480
                    }
                },
                "description": "When your friend has a robot arm in another state, you find a way to use it. Watch how Matías and David used Gemini to bridge 1,700 miles, building custom 3D web controllers that operate physical hardware in real time. \n\n🔗 Explore the build → https://goo.gle/3U909Gu\n\n\nSubscribe to Google for Developers → https://goo.gle/developers   \n\n\nProducts Mentioned: Gemini, Google Antigravity, Google AI Studio\nSpeakers: Matías Piña Aguilera, David Maliglowka",
                "publishedAt": "2026-10-09T19:00:36+00:00",
                "channelTitle": "Google for Developers"
            }
        },
        {
            "id": "MTUxNzkxNTYxNjEwMTc5MTU2MTYxMDAwMDE0OQ",
            "etag": "q74Shg4Og0pnCdxeg_6TTucbt2k",
            "kind": "youtube#activity",
            "snippet": {
                "type": "upload",
                "title": "Building low-latency remote robotics with Gemini",
                "channelId": "UC_x5XG1OV2P6uZZ5FSM9Ttw",
                "thumbnails": {
                    "fhd": {
                        "url": "https://i.ytimg.com/vi/7sKHiuE7J-Y/fhddefault.jpg",
                        "width": 1920,
                        "height": 1080
                    },
                    "high": {
                        "url": "https://i.ytimg.com/vi/7sKHiuE7J-Y/hqdefault.jpg",
                        "width": 480,
                        "height": 360
                    },
                    "maxres": {
                        "url": "https://i.ytimg.com/vi/7sKHiuE7J-Y/maxresdefault.jpg",
                        "width": 1280,
                        "height": 720
                    },
                    "medium": {
                        "url": "https://i.ytimg.com/vi/7sKHiuE7J-Y/mqdefault.jpg",
                        "width": 320,
                        "height": 180
                    },
                    "default": {
                        "url": "https://i.ytimg.com/vi/7sKHiuE7J-Y/default.jpg",
                        "width": 120,
                        "height": 90
                    },
                    "standard": {
                        "url": "https://i.ytimg.com/vi/7sKHiuE7J-Y/sddefault.jpg",
                        "width": 640,
                        "height": 480
                    }
                },
                "description": "Working 1,700 miles apart, Matías and David used Google Antigravity, Google AI Studio, and Gemini to construct a remote robotics framework powered by custom 3D web controllers.\n\nWatch to discover how they implemented low-latency hardware controls to operate physical machinery across thousands of miles.\n\nTry building today → https://goo.gle/4ya3rr3\n\n\nSubscribe to Google for Developers → https://goo.gle/developers   \n\n\nProducts Mentioned: Gemini, Google Antigravity, Google AI Studio\nSpeakers: Matías Piña Aguilera, David Maliglowka",
                "publishedAt": "2026-10-09T16:00:10+00:00",
                "channelTitle": "Google for Developers"
            }
        },
        {
            "id": "MTUxNzkxNTAwNDA5MTc5MTUwMDQwOTAwMDMwNw",
            "etag": "S7afJ-PBklFZOz8S4mXbyIKC64c",
            "kind": "youtube#activity",
            "snippet": {
                "type": "upload",
                "title": "Building with Gemma 4",
                "channelId": "UC_x5XG1OV2P6uZZ5FSM9Ttw",
                "thumbnails": {
                    "qhd": {
                        "url": "https://i.ytimg.com/vi/fL9OBJO3Gu8/qhddefault.jpg",
                        "width": 2560,
                        "height": 1440
                    },
                    "high": {
                        "url": "https://i.ytimg.com/vi/fL9OBJO3Gu8/hqdefault.jpg",
                        "width": 480,
                        "height": 360
                    },
                    "maxres": {
                        "url": "https://i.ytimg.com/vi/fL9OBJO3Gu8/maxresdefault.jpg",
                        "width": 1280,
                        "height": 720
                    },
                    "medium": {
                        "url": "https://i.ytimg.com/vi/fL9OBJO3Gu8/mqdefault.jpg",
                        "width": 320,
                        "height": 180
                    },
                    "default": {
                        "url": "https://i.ytimg.com/vi/fL9OBJO3Gu8/default.jpg",
                        "width": 120,
                        "height": 90
                    },
                    "standard": {
                        "url": "https://i.ytimg.com/vi/fL9OBJO3Gu8/sddefault.jpg",
                        "width": 640,
                        "height": 480
                    }
                },
                "description": "Gemma 4 is the most capable model family you can run on your hardware. They complement our Gemini models, giving our developer community the industry's most powerful combination of both open and proprietary tools. Watch for inspiration for your next Gemma build, or even just to get to know Reachy the offline robot (running LFG-3 on a Reachy Mini and NVIDIA DGX Spark). \n\nLearn more about Gemma here: https://goo.gle/4dxj30m, and share what you’ll build with an AI model that runs directly on-device in the comments below! \n\n\n🔗Resources:\n\nCommunity Builds Featured in this Video \n*Wearable Robotic Arm →  https://goo.gle/4rVOib9\n*PenguinAgent → https://goo.gle/3VVfTNO\n*CodeBuddy (Offline Coding) → https://goo.gle/4y9tRsM\n\nModels & Open Source Attributions\n*Custom Model: LFG-3 → https://goo.gle/3UbydBQ\n*Speech Recognition: LFG-3 fuses NVIDIA Parakeet → https://goo.gle/3TTzn4T, licensed under CC BY 4.0 → https://goo.gle/4ic5Tby \n*Text-to-Speech: This project uses Kyutai TTS 1.6B → https://goo.gle/4hBVrtR, licensed under CC BY 4.0 → https://goo.gle/4ic5Tby\n\n\nSubscribe to Google for Developers → https://goo.gle/developers    \n\n\n\nSpeakers: Glenn Cameron\nProducts Mentioned: Gemma",
                "publishedAt": "2026-10-08T23:00:09+00:00",
                "channelTitle": "Google for Developers"
            }
        }
    ],
    "pageInfo": {
        "totalResults": 20,
        "resultsPerPage": 5
    },
    "nextPageToken": "CAUQAA"
}

Errors

StatusMeaningCharged?
401Missing, invalid or revoked API keyNo
402Not enough credits (insufficient_credits)No
404The account or post doesn't existNo
422Missing or invalid parametersNo
502 / 503The data source is temporarily unavailableNo

All error codes →

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