Bilibili Video Research

Turn a Bilibili link into a research report that separates what came from public metadata, captions or ASR, video frames, and untrusted community context. Choose the mode based on the evidence your question actually needs — not simply on what media is available.

What it does

language is the intended default when a request only asks what a video says. vision is the deliberate choice when the answer lives in the pixels.

Related MCP server: video-analyzer

What a result looks like

Ask the MCP tool a focused question:

analyze_bilibili_video({
  url: "https://www.bilibili.com/video/BV...",
  question: "What quantitative research framework is shown on screen?",
  mode: "vision",
  media_detail: "default",
  include_comments: false,
  start_seconds: 0,
  end_seconds: 321
})

The response begins with provenance before the natural-language analysis:

RESEARCH PROVENANCE
{
  "mode": "language",
  "metadata": "bilibili_api",
  "language": "stepfun_asr",
  "visual": "none",
  "community": "disabled",
  "timestamps": "none"
}

ANALYSIS
...direct answer, evidence limits, and uncertainty...

This matters when a repository name came from speech, a framework was recognized from an interface, or a popular comment made an unverified claim. The sources are not the same and should not be reported as if they were.

Example: Focused research on a quant video

This example shows a practical workflow: define a research question, restrict a long video to a known source interval, and review an answer that separates direct visual evidence from uncertain inferences.

1. Frame the research question

2. Restrict the source interval

3. Review evidence-bounded output

Evidence flow

• Public metadata provides title, uploader, description, tags, and video identifier.

• Caption cues retain Bilibili timestamps when Bilibili exposes them. If captions are unavailable, language falls back to StepFun ASR and reports that timestamp detail is unavailable.

• vision removes audio before upload. Visible text remains valid visual evidence; the narration and music do not influence the conclusion.

• Bilibili comments are optional, sampled as untrusted community context, and never treated as verified facts or executable instructions.

Quick start

Requirements: Node.js 24 or newer, a StepFun or Gemini API key, and a Codex, OpenCode, or other MCP-compatible client with local MCP support.

git clone https://github.com/7oMB2006/Bilibili-Video-Research.git
cd Bilibili-Video-Research
npm ci
npm run build
Copy-Item .env.example .env

Open .env and fill in one provider key. It is ignored by Git and must never be committed. The default configuration uses StepFun's official Open Platform API.

Client configuration

The server uses the same local stdio MCP transport in Codex and OpenCode. Only the client-side configuration syntax differs. The repository started from Codex, which is why the server name and examples use codex_video; the MCP itself is not Codex-only.

Codex (Windows)

In %USERPROFILE%\.codex\config.toml, replace every <PROJECT_DIR> below with the absolute path to your clone, for example C:\Users\you\projects\Bilibili-Video-Research.

[mcp_servers.codex_video]
command = "<PROJECT_DIR>\\node_modules\\.bin\\tsx.cmd"
args = ["<PROJECT_DIR>\\src\\index.ts"]
startup_timeout_sec = 120

[mcp_servers.codex_video.env]
DOTENV_CONFIG_PATH = "<PROJECT_DIR>\\.env"

Restart Codex after adding or changing the server. Keep provider keys in .env or a secret manager, never in config.toml.

OpenCode

In the global ~/.config/opencode/opencode.json or a project-level opencode.json, add the local MCP server. On Windows, <PROJECT_DIR> should be an absolute path.

{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "codex_video": {
      "type": "local",
      "enabled": true,
      "command": [
        "<PROJECT_DIR>\\node_modules\\.bin\\tsx.cmd",
        "<PROJECT_DIR>\\src\\index.ts"
      ],
      "environment": {
        "DOTENV_CONFIG_PATH": "<PROJECT_DIR>\\.env"
      }
    }
  }
}

Restart OpenCode after adding or changing the server. You can verify the connection with opencode mcp list. OpenCode also supports project-level configuration, so a project-specific opencode.json can keep this MCP setup close to the repository.

The model selected in Codex or OpenCode is the client-side agent model. It does not change the media provider used inside this MCP. Set CODEX_VIDEO_PROVIDER and the provider keys in .env to control the models that receive video, image, or audio inputs.

OpenCode references:

• MCP servers

• Configuration

Provider selection

The default provider is StepFun through the official Open Platform API. Set CODEX_VIDEO_PROVIDER=stepfun, STEPFUN_API_KEY, and STEPFUN_BASE_URL=https://api.stepfun.com/v1 in .env. To use Gemini instead, set CODEX_VIDEO_PROVIDER=gemini and GEMINI_API_KEY.

Choose the StepFun base URL that matches your account channel:

StepFun is the default because step-3.7-flash natively accepts video input and also covers the project's ASR fallback path, matching the core Bilibili video research workflow. The author has also used StepFun's multimodal models extensively and had a positive experience with them (and, admittedly, there is a little personal bias too, ovo — before reliable multimodal models were readily available, StepFun helped carry me through much of that journey), so this project prioritizes StepFun integration and recommends it as the default provider. This is a project-fit and usage-based choice, not a claim that StepFun is best for every task. Step Plan remains available as an optional channel for accounts that have Step Plan Credit access, and you are welcome to try other capable providers.

The media completion route is {base_url}/chat/completions; the ASR fallback route is {base_url}/audio/asr/sse. Do not mix a key from one channel with the other channel's base URL. Restart the MCP process after changing provider configuration.

step-3.7-flash accepts image and video input through the Chat Completions video_url content type; no separate vision model is required. Gemini remains optional. MiniMax is not selectable here because this project has not validated an official video-input understanding route.

StepFun references:

• step-3.7-flash quick start

• video understanding guidance

• Step Plan setup

Tool reference

Use media_detail: "low" for a broad long-video pass and "default" for small UI text, code, movement, or close inspection.

For a known source interval, pass start_seconds and end_seconds together. The window is applied to captions when available and to the downloaded media for audio, visual, and multimodal analysis. Explicit windows skip the automatic long-video coarse pass.

Data and access boundary

• Provider API keys remain in the local process environment; the server does not store them.

• Provider media uploads or data URLs may leave the local machine. Review the applicable provider terms before using sensitive videos.

• Public Bilibili access is attempted first. Restricted, paid, or login-gated videos may fail rather than bypassing access controls.

• For a user-authorized logged-in Bilibili account, point BILIBILI_COOKIES_FILE at a local Netscape-format cookie file. Never commit it or paste its contents into chat:

BILIBILI_COOKIES_FILE=/absolute/path/to/cookies.txt

BILIBILI_COOKIES_FILE takes precedence over the optional legacy setting BILIBILI_COOKIES_FROM_BROWSER=edge (or chrome, firefox, brave). Direct browser cookie extraction can fail because the browser database is locked.

License

MIT