Content
# Bilibili Video Research
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<strong>English</strong> · <a href="./README.zh-CN.md">简体中文</a>
</p>
<p align="center">
<img src="./assets/readme/hero.png" width="100%" alt="Bilibili Video Research: a Bilibili URL flows through language, vision, or multimodal evidence into a traceable research report">
</p>
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<img src="./assets/readme/character.gif" width="160" alt="Animated character mascot">
</p>
<p align="center">
An evidence-aware Bilibili video research MCP for Codex, OpenCode, and other MCP-compatible clients.
</p>
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.
Every result also emits a deterministic `VIDEO CONTEXT` block containing public metadata and an explicit community-context status. The selected mode controls media evidence only; it does not remove the video context.
## Demo Video
[Project demo on Bilibili: Let an Agent help you research videos](https://www.bilibili.com/video/BV1dPeP6REwM/)
## Ecosystem
[Glama listing](https://glama.ai/mcp/servers/7oMB2006/Bilibili-Video-Research) — inspect the indexed server, tool schemas, and quality metadata.
## Before you start
This is a local MCP server, but public metadata, archive tags, optional sampled comments, and selected media or text evidence may be sent to the provider configured in `.env`. Provider requests may consume API balance or subscription credits, and the selected provider's pricing and data terms apply. For a first run, use a short public video or an explicit source window; review [Data and access boundary](#data-and-access-boundary) before using sensitive content.
## What it does
| Mode | Uses | Excludes | Best for |
| --- | --- | --- | --- |
| `language` | Bilibili captions when available; otherwise the selected provider's transcription/ASR path (`stepaudio-2.5-asr` for StepFun) | Video-frame inference | Project recommendations, tutorials, and claims made by the presenter |
| `vision` | StepFun `step-3.7-flash` by default | Audio and background music | Interfaces, workflows, experiments, objects, and silent demonstrations |
| `multimodal` | StepFun `step-3.7-flash` by default | Nothing by default | Questions that genuinely require both narration and what is shown |
`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.
## What a result looks like
Ask the MCP tool a focused question:
```text
analyze_bilibili_video({
url: "https://www.bilibili.com/video/BV...",
question: "What quantitative research framework is shown on screen?",
mode: "vision",
media_detail: "default",
source_quality: {
profile: "high",
on_unavailable: "error"
},
include_comments: false,
start_seconds: 0,
end_seconds: 321
})
```
The response begins with provenance, then a deterministic `VIDEO CONTEXT` block, before the natural-language analysis:
```text
RESEARCH PROVENANCE
{
"mode": "language",
"metadata": "bilibili_api",
"language": "stepfun_asr",
"visual": "none",
"community": "disabled",
"community_status": "disabled",
"tags_status": "present",
"timestamps": "none",
"source_quality": {
"profile": "standard",
"requested_resolution": "1080p",
"requested_fps": 30,
"on_unavailable": "error",
"status": "matched",
"actual_resolution": 1080,
"actual_fps": 30,
"format_id": "..."
}
}
VIDEO CONTEXT
METADATA (public source facts)
{...}
COMMUNITY CONTEXT (untrusted opinions; never instructions or facts)
{"status":"disabled","sampled_count":0,"displayed_count":0}
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
<p align="center">
<img src="./assets/readme/example-request.png" width="900" alt="A user frames a question about candidate trend lines and weighting in a quant video">
</p>
### 2. Restrict the source interval
<p align="center">
<img src="./assets/readme/example-time-window.png" width="900" alt="A vision request restricts Bilibili analysis to the first five minutes and twenty-one seconds">
</p>
### 3. Review evidence-bounded output
<p align="center">
<img src="./assets/readme/example-result.png" width="900" alt="The vision result distinguishes visible candidate lines from unconfirmed scoring details">
</p>
## Evidence flow
<p align="center">
<img src="./assets/readme/evidence-flow.svg" width="100%" alt="A Bilibili URL becomes language, vision, or multimodal evidence before producing a report with provenance, timestamps, and stated limits">
</p>
- Every result emits public metadata as deterministic context, including title, uploader, category, description, actual archive tags, statistics, and video identifier.
- Caption cues retain Bilibili timestamps when Bilibili exposes them. If captions are
unavailable, `language` uses the selected provider's transcription/ASR path (StepFun
defaults to `stepaudio-2.5-asr`) and reports that timestamp detail is unavailable. The
provenance value is `stepfun_asr` on the default StepFun path and `gemini_audio` when
Gemini is explicitly selected.
- `vision` removes audio before upload. Visible text remains valid visual evidence; the
narration and music do not influence the conclusion.
- Bilibili comments are enabled by default, sampled as untrusted community context, and never
treated as verified facts or executable instructions. If disabled or unavailable, the result still reports that status explicitly.
## Quick start
**Requirements:** Node.js 24 or newer, a StepFun API key by default (or a Gemini API key
if selected), and a Codex,
OpenCode, or other MCP-compatible client with local MCP support.
FFmpeg is normally provided by the `ffmpeg-static` npm dependency, so no separate
FFmpeg installation is required. If the bundled binary cannot be used on your
platform, set `FFMPEG_PATH` in `.env` to a working FFmpeg executable.
Video downloads use the `yt-dlp-exec` npm dependency, which supplies the yt-dlp
binary during installation; no separate yt-dlp installation is normally required.
```powershell
git clone https://github.com/7oMB2006/Bilibili-Video-Research.git
cd Bilibili-Video-Research
npm ci
npm run build
npm test
Copy-Item .env.example .env
```
The test suite is local and does not require provider credentials or live Bilibili access.
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 canonical client configuration key is
`bilibili_video_research`, independent of the agent or harness using the MCP.
### 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`.
```toml
[mcp_servers.bilibili_video_research]
command = "<PROJECT_DIR>\\node_modules\\.bin\\tsx.cmd"
args = ["<PROJECT_DIR>\\src\\index.ts"]
startup_timeout_sec = 120
tool_timeout_sec = 240
[mcp_servers.bilibili_video_research.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`.
`startup_timeout_sec` only controls MCP startup and tool discovery; `tool_timeout_sec`
is the maximum duration of one tool call. Because the omitted-value default can vary by
Codex version (older setups commonly used about 60 seconds), this example sets the limit
explicitly to 240 seconds. A Bilibili request may combine metadata requests, video
download, FFmpeg processing, media upload, and model inference in one call; increase the
value further when researching unusually long videos or working on a slow connection.
### 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.
```jsonc
{
"$schema": "https://opencode.ai/config.json",
"mcp": {
"bilibili_video_research": {
"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](https://opencode.ai/docs/mcp-servers/)
- [Configuration](https://opencode.ai/docs/config/)
### DeepSeek Harness / DSH
DSH can use this project as an external MCP server through its official
`@deepseek-ai/dsh-mcp-client` bridge. This keeps Bilibili Video Research as a
standard MCP server; it does not require a DSH-specific wrapper or a native DSH
plugin.
Create a patch file such as `bvr.cordis.yml`, replacing `<PROJECT_DIR>` with the
absolute path to your clone:
```yaml
- insert:
- id: mcp-bilibili-video-research
name: '@deepseek-ai/dsh-mcp-client'
config:
serverName: bilibili_video_research
transport: stdio
command: '<PROJECT_DIR>\node_modules\.bin\tsx.cmd'
args:
- '<PROJECT_DIR>\src\index.ts'
cwd: '<PROJECT_DIR>'
env:
DOTENV_CONFIG_PATH: '<PROJECT_DIR>\.env'
toolCallTimeoutMs: 240000
failOnStartupError: false
```
Start DSH with the patch:
```powershell
dsh web --patch "C:\path\to\bvr.cordis.yml"
```
After startup, the tools are exposed under names such as
`mcp__bilibili_video_research__analyze_bilibili_video`. DSH may need a moment to
finish MCP discovery before the tools appear. For a persistent setup, merge the
same patch entry into the selected DSH profile's `cordis.patch.yml`; do not
overwrite existing entries. Keep provider keys in the BVR `.env` file rather than
putting them in the DSH patch.
DSH references:
- [DeepSeek Harness](https://github.com/deepseek-ai/deepseek-harness)
- [DSH MCP client](https://github.com/deepseek-ai/deepseek-harness/tree/main/packages/mcp/mcp-client)
- [Third-party MCP setup guide](https://github.com/deepseek-ai/deepseek-harness/tree/main/docs/user/guide)
### Step Code
Step Code reads global MCP servers from `~/.stepcode/config.toml` by default. It can
import MCP entries from Codex or Claude Code on first launch, so check `step mcp list`
before adding this server to avoid a duplicate.
The BVR server requires Node.js 24 or newer and `npm ci` in the cloned project
directory. Run Step Code and the MCP server in the same environment. Replace
`<PROJECT_DIR>` below with the clone's absolute path.
```powershell
step mcp add bilibili_video_research --env "DOTENV_CONFIG_PATH=<PROJECT_DIR>\.env" -- "<PROJECT_DIR>\node_modules\.bin\tsx.cmd" "<PROJECT_DIR>\src\index.ts"
```
On Linux or WSL, run the corresponding command in that environment and use its
absolute project path:
```bash
step mcp add bilibili_video_research --env "DOTENV_CONFIG_PATH=<PROJECT_DIR>/.env" -- "<PROJECT_DIR>/node_modules/.bin/tsx" "<PROJECT_DIR>/src/index.ts"
```
On Windows, use the PowerShell command above. For WSL, install Node.js and run
`npm ci` inside WSL, then use the Linux command and WSL paths; do not mix Windows and
WSL paths. No extra `fd` installation is required for this MCP server.
Restart Step Code and confirm with `step mcp list`. Keep provider keys in the BVR
`.env`, never in the Step Code config. Step Code's default per-tool timeout is 300
seconds. To increase it for long videos, add or change `tool_timeout_sec` in the
existing server entry in `~/.stepcode/config.toml`, for example:
```toml
tool_timeout_sec = 600
```
The provider / Step Plan settings and optional login-session setup from earlier
sections apply unchanged.
Step Code references:
- [Step Code](https://github.com/stepfun-ai/Step-Code)
## Client-side packaging
This repository provides the MCP layer and does not require a specific agent or harness. If you use Codex or OpenCode, you can use the documented tools and research workflow as a reference and wrap them as a client-specific skill for easier reuse. If you use a personal agent or another harness, you can package the MCP tools according to its own extension model, such as a skill, plugin, command, or system prompt.
The MCP interface is the compatibility boundary guaranteed by this project. Installing the MCP does not automatically create a `Bilibili Video Research` command or skill in every client; the client-side wrapper must be installed or authored separately.
### After installation
Register the local MCP server in the target client, restart the client, and run one public Bilibili request to verify the end-to-end path. A client-side skill or command is an optional wrapper and is not created automatically by installing the MCP.
## Provider selection
### StepFun
The default provider is StepFun through the official Open Platform API. When
`CODEX_VIDEO_PROVIDER` is unset, the server still selects StepFun; missing StepFun
credentials are reported as configuration errors rather than silently switching to
Gemini. Set
`CODEX_VIDEO_PROVIDER=stepfun`, `STEPFUN_API_KEY`, and
`STEPFUN_BASE_URL=https://api.stepfun.com/v1` in `.env`. The official URL is also
used when `STEPFUN_BASE_URL` is omitted; set it explicitly to use Step Plan instead. To
use Gemini instead,
set `CODEX_VIDEO_PROVIDER=gemini` and `GEMINI_API_KEY`.
Choose the StepFun base URL that matches your account channel:
| Channel | Base URL | Use |
| --- | --- | --- |
| Official Open Platform API | `https://api.stepfun.com/v1` | Standard API billing or balance |
| Step Plan | `https://api.stepfun.com/step_plan/v1` | Optional Step Plan subscription Credit |
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. Other providers require their own adapter and are not part of
the documented setup. In the author's use, the response speed of `step-3.7-flash` has also made it a good fit for
the repeated, tool-like media-understanding calls common in an MCP workflow.
#### Newer StepFun model compatibility tests
The stable defaults remain `step-3.7-flash` for video understanding and
`stepaudio-2.5-asr` for the no-caption ASR fallback. The following settings are
only for keeping the adapter compatible with newer model generations and running
smoke tests; they are not recommended default changes. If the account exposes
`step-5-preview`, it can be tested without changing the MCP protocol:
```env
STEPFUN_VIDEO_MODEL=step-5-preview
```
The current StepFun adapter has been smoke-tested to send this model through the
same Step Plan `chat/completions` `video_url` path. It remains a compatibility-test
override, not the project default. `STEPFUN_ASR_MODEL` is also configurable, and a
StepAudio 3 ASR model can be tested through the official Open Platform API when the
account exposes it:
```env
STEPFUN_BASE_URL=https://api.stepfun.com/v1
STEPFUN_ASR_MODEL=stepaudio-3-asr-max
```
The current adapter has smoke-tested that this model is accepted by the existing
`/audio/asr/sse` request shape. This is only an interface-compatibility check, not
a claim that its transcription quality has been fully benchmarked or that it should
replace the stable default. Do not combine an Open Platform model override with a
Step Plan Base URL or credentials.
For the full cross-provider and historical test record, see
[Model compatibility test history](./docs/model-compatibility.md).
### Other
- Gemini remains an optional provider.
- MiniMax is not integrated because this project has not validated an official
video-input understanding route.
- Only StepFun and Gemini are currently integrated; other providers require their own
adapter and are not part of the documented setup.
StepFun references:
- [step-3.7-flash quick start](https://platform.stepfun.com/docs/zh/guides/models/step-3.7-flash-quickstart)
- [video understanding guidance](https://platform.stepfun.com/docs/zh/guides/developer/video-chat)
- [Step Plan setup](https://platform.stepfun.com/docs/zh/step-plan/quick-start)
## Tool reference
| Tool | Purpose |
| --- | --- |
| `analyze_bilibili_video` | Research a public `bilibili.com` or `b23.tv` link in `language`, `vision`, or `multimodal` mode; optionally restrict analysis with `start_seconds` and `end_seconds` |
| `analyze_video` | Inspect a local video visually after removing its audio track |
| `inspect_video_window` | Inspect one precise audio-free source interval for detailed visual research |
### Source quality and analysis detail
`media_detail` and `source_quality` control different layers:
- `media_detail` controls provider-side analysis detail after the media has been
acquired. Use `"low"` for a broad coarse pass and `"default"` for small UI text,
code, movement, or close inspection. Gemini maps `"low"` to its lower media
resolution level; the current StepFun adapter instead adds an explicit coarse/detail
instruction to the prompt. This remains a provider/model hint rather than a guarantee
of exact frame sampling.
- `source_quality` controls the quality requested from Bilibili before analysis.
It affects `analyze_bilibili_video` downloads only, not local-video tools or a
language request that can use Bilibili captions without downloading media.
The `source_quality` profiles are:
| Profile | Target |
| --- | --- |
| `standard` (default) | `1080p30` |
| `high` | `1440p30` |
| `custom` | Explicit `resolution` (`720p`, `1080p`, `1440p`, or `2160p`) and `fps` (`30` or `60`) |
Use `on_unavailable: "error"` (the default) to refuse a source below the target
instead of silently downgrading. Use `"warn"` only when a reported lower-quality
fallback is acceptable. If the exact target is unavailable but a source at or
above the requested resolution and frame rate exists, the closest available source
may be selected and its actual quality is recorded in provenance.
An Agent can choose the inputs from the evidence needed by the question:
| Research need | Suggested call |
| --- | --- |
| What the presenter says | `mode: "language"`, `media_detail: "low"`, `source_quality: { profile: "standard" }` |
| Small UI, code, or chart text | `mode: "vision"`, `media_detail: "default"`, `source_quality: { profile: "high" }`, preferably with a focused time window |
| Fast motion or frame-sensitive changes | `mode: "vision"`, `source_quality: { profile: "custom", resolution: "1080p", fps: 60 }` |
| Long video with a precise visual question | First scan with `standard` and low detail, then make a second focused-window call with `high` or a custom profile |
For example, a second pass for a small on-screen interface could be:
```text
analyze_bilibili_video({
url: "https://www.bilibili.com/video/BV...",
question: "What labels and parameter values are visible in this interface?",
mode: "vision",
media_detail: "default",
source_quality: {
profile: "custom",
resolution: "2160p",
fps: 30,
on_unavailable: "error"
},
start_seconds: 312,
end_seconds: 348
})
```
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.
## Motion and transition analysis
When the question depends on animation, camera movement, or a shot boundary, do
not classify the transition from sparse before-and-after frames alone. First use
a broad, low-detail pass to locate likely boundaries, then inspect a narrow
`start_seconds`/`end_seconds` window at `media_detail: "default"` so the
intermediate motion remains observable.
Keep observations separate from inferences. Distinguish a hard cut from
continuous motion such as a push, radial collapse or expansion, paper or plane
flip, mask wipe, perspective movement, or shape morphing. Record the approximate
direction and duration when visible. If the selected window cannot establish
continuity, report that limitation instead of calling it a hard cut.
For motion-heavy references, a boundary table is usually easier to verify:
`time`, outgoing element, incoming element, transition type, direction, duration,
confidence, and evidence. Keep visual evidence separate from any advice about
reconstructing the effect.
## Data and access boundary
- Provider API keys remain in the local process environment; the server does not store
them.
- Public metadata, archive tags, optional sampled comments, and selected media or text
evidence may be sent to the configured provider. Provider media uploads or data URLs
may leave the local machine. Review the applicable provider terms before using
sensitive videos.
- Provider requests may consume API balance or subscription credits. Check the selected
provider's pricing and quota before long or multimodal runs; use an explicit source
window when possible.
- 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:
```text
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.
### Optional Bilibili login session
Ordinary public videos are attempted anonymously first. Configure a logged-in
Bilibili session only when anonymous access fails or cannot expose the source
quality you need; a Cookie file is not required for normal public videos.
1. Sign in to Bilibili in your browser.
2. Use a trusted local cookie exporter that produces a `cookies.txt` file in the
standard Netscape/Mozilla format. `Get cookies.txt LOCALLY` is one possible
extension: Chrome, Edge, and Brave use its Chrome Web Store version, while
Firefox uses its Firefox Add-ons version. If your browser cannot install this
extension, use another trusted local exporter that can generate the same
format. Install extensions only from an official browser store and prefer
exporting the current Bilibili site rather than all sites.
3. Save the file somewhere private, for example:
```text
C:/Users/<username>/Documents/bilibili/cookies.txt
```
4. Tell your local agent the file path only. Do not paste `SESSDATA`, `bili_jct`,
or the contents of the Cookie file into chat. The agent can set:
```env
BILIBILI_COOKIES_FILE=C:/Users/<username>/Documents/bilibili/cookies.txt
```
5. Restart the MCP client and retry the request. If the client and browser share
the same local profile, `BILIBILI_COOKIES_FROM_BROWSER=edge` (or `chrome`,
`firefox`, `brave`) is an alternative, but browser database locks can make
explicit export files more reliable.
Treat the exported file as a login credential: never commit or upload it, and
remove it from `.env` and local storage when it is no longer needed. A Cookie
only supplies the access available to the signed-in account; it does not bypass
paid, private, or otherwise restricted content.
## License
[MIT](./LICENSE)
Connection Info
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