TMDB Server

平台与服务

by Laksh-star

通过集成 The Movie Database(TMDB)API,提供电影信息查询、搜索能力和个性化推荐。

什么是 TMDB Server

通过集成 The Movie Database(TMDB)API,提供电影信息查询、搜索能力和个性化推荐。

核心功能 (3 个工具)

search_movies

Search for movies by title or keywords

get_recommendations

Get movie recommendations based on a movie ID

get_trending

Get trending movies for a time window

README

TMDB MCP Server

An MCP server for The Movie Database (TMDB) API. It provides movie and TV search, streaming availability, cast and crew details, and recommendations for assistants such as Codex and Claude Desktop.

For the architecture split between the reusable MCP server and higher-level feature workflows, see USERGUIDE.md.

Tools

Movie Discovery

  • get_weekend_watchlist — Ranked weekend shortlist by mood, country, language, runtime, rating, and services
  • plan_watch_party — Group movie-night plan with a primary pick, backup, wildcard, party-fit reasons, provider availability, and avoided-title filtering
  • build_franchise_watch_order — Franchise/universe guide with release order, suggested order, total runtime, and provider-aware notes
  • build_collection_gap_plan — Franchise completion plan with watched/missing entries, remaining runtime, provider availability, and completion path
  • recommend_from_taste_profile — Recommendations from liked/disliked titles with provider-aware scoring, match reasons, and cautions
  • search_movies — Search by title/keywords → titles, IDs, ratings, overviews
  • get_trending — Top 10 trending movies (timeWindow: "day" | "week")
  • get_weekly_trending_by_language — Weekly trending movies grouped by original language into English, Hindi, and Telugu
  • search_by_genre — Movies by genre name, optional year filter
  • advanced_search — Filter by genre, year, min rating, sort, language
  • search_by_keyword — Find movies by theme/keyword (e.g. "zombie", "heist")

Movie Details

  • get_movie_details — Full details: cast, crew, runtime, genres, reviews (by movieId)
  • compare_movies — Side-by-side comparison for 2-5 movie IDs with ratings, runtime, cast, director, providers, and best-fit notes
  • get_recommendations — Top 5 recommendations based on a movie ID
  • get_similar_movies — Similar movies via TMDB's similarity algorithm
  • get_watch_providers — Streaming/rental/purchase availability by country (default: IN)
  • find_where_to_watch — Search 1-5 movie titles and return streaming/rental/purchase availability with preferred-service matches

TV Shows

  • search_tv_shows — Search TV series by title
  • get_trending_tv — Top 10 trending TV shows (timeWindow: "day" | "week")

People

  • search_person — Find actors, directors, crew by name → ID + known works
  • get_person_details — Full bio + filmography (movies + TV) by personId
  • build_person_watch_path — Actor/director watch path with best-rated, available-now, recent, and starter picks

Resources

  • tmdb:///movie/<id> — Full movie details in JSON (title, cast, director, reviews, poster URL)

Quick Start

  1. Get a TMDB API key at themoviedb.org → Account Settings → API

  2. Clone, install, and build:

    bash
    git clone https://github.com/Laksh-star/mcp-server-tmdb.git
    cd mcp-server-tmdb
    npm install
    
  3. Create a local env file and add your TMDB key:

    bash
    cp .env.example .env
    
  4. Install the local Codex and Claude Desktop integration:

    bash
    npm run install:local
    
  5. Restart Codex or Claude Desktop if already open.

  6. Verify with a prompt like:

    text
    What movies are trending this week?
    

In Codex, a fresh session should show TMDB in the plugin list and expose the mcp__tmdb__ namespace.

Tool Surface Smoke

Use this smoke test after adding or merging tools. It verifies the expected MCP tool contract and calls the main workflow tools: compare_movies, find_where_to_watch, get_weekend_watchlist, plan_watch_party, build_franchise_watch_order, build_collection_gap_plan, recommend_from_taste_profile, and build_person_watch_path.

Local stdio MCP:

bash
npm run build
set -a && source ./.env && set +a && npm run smoke:tools

Cloudflare-hosted MCP:

bash
TMDB_MCP_ACCESS_TOKEN=<your-access-token> node scripts/tool-surface-smoke.mjs --mcp-url https://tmdb-mcp.<your-workers-subdomain>.workers.dev/mcp

The script writes a compact verification artifact to:

text
examples/tool-surface-smoke.md

To avoid tool bloat, prefer adding workflow tools that combine multiple TMDB calls into a useful user decision. Keep raw endpoint-style tools only when they are broadly reusable primitives.

Weekly Trending Language Demo

This repo includes a small shareable demo that calls the MCP tool get_weekly_trending_by_language, which fetches live TMDB weekly trending movies and groups the current first page by TMDB original_language.

Run it against the local stdio MCP server:

bash
npm run build
set -a && source ./.env && set +a && npm run demo:weekly-trending

After deploying this version of the Worker, run the same demo against a remote MCP endpoint:

bash
TMDB_MCP_ACCESS_TOKEN=<your-access-token> node scripts/weekly-trending-languages.mjs --mcp-url https://tmdb-mcp.<your-workers-subdomain>.workers.dev/mcp

If the deployment is intentionally authless for personal testing, omit TMDB_MCP_ACCESS_TOKEN.

Weekly Streaming Radar

This repo also includes a script-first weekly radar. It chains existing MCP tools into a Markdown artifact with movie trends, TV trends, language momentum, action-ready picks, family-safe picks, and a taste-profile probe.

Local stdio MCP:

bash
npm run build
set -a && source ./.env && set +a && npm run demo:weekly-radar -- --country US

Cloudflare-hosted MCP:

bash
TMDB_MCP_ACCESS_TOKEN=<your-access-token> node scripts/weekly-streaming-radar.mjs --mcp-url https://tmdb-mcp.<your-workers-subdomain>.workers.dev/mcp --country US

The script writes:

text
examples/weekly-streaming-radar.md

Release Calendar Watchlist

The release calendar is also script-first. It creates a Markdown artifact for upcoming or recent release-window scanning, watch-later candidates, family-safe baselines, and provider probes.

Local stdio MCP:

bash
npm run build
set -a && source ./.env && set +a && npm run demo:release-calendar -- --country US --days 90

Cloudflare-hosted MCP:

bash
TMDB_MCP_ACCESS_TOKEN=<your-access-token> node scripts/release-calendar-watchlist.mjs --mcp-url https://tmdb-mcp.<your-workers-subdomain>.workers.dev/mcp --country US --days 90

The script writes:

text
examples/release-calendar-watchlist.md

Provider Change Monitor

The provider monitor is script-first because it needs persisted state. It calls find_where_to_watch, compares the current provider list against a JSON snapshot, and writes a Markdown delta report showing new, removed, unchanged, and missing provider availability.

Local stdio MCP:

bash
npm run build
set -a && source ./.env && set +a && npm run demo:provider-monitor -- --country US --titles "The Matrix,Inception" --services "Netflix,Prime Video"

Cloudflare-hosted MCP:

bash
TMDB_MCP_ACCESS_TOKEN=<your-access-token> node scripts/provider-change-monitor.mjs --mcp-url https://tmdb-mcp.<your-workers-subdomain>.workers.dev/mcp --country US --titles "The Matrix,Inception" --services "Netflix,Prime Video"

The script writes:

text
examples/provider-change-monitor.md
examples/provider-change-snapshot.json

Collection Gap Finder

The collection gap finder script now calls the promoted MCP tool build_collection_gap_plan and writes a repeatable Markdown completion report with watched entries, missing entries, remaining runtime, provider availability, and a shortest completion path.

Local stdio MCP:

bash
npm run build
set -a && source ./.env && set +a && npm run demo:collection-gaps -- --franchise "The Matrix" --watched "The Matrix" --country US --services "Netflix,Prime Video"

Cloudflare-hosted MCP:

bash
TMDB_MCP_ACCESS_TOKEN=<your-access-token> node scripts/collection-gap-finder.mjs --mcp-url https://tmdb-mcp.<your-workers-subdomain>.workers.dev/mcp --franchise "The Matrix" --watched "The Matrix" --country US --services "Netflix,Prime Video"

The script writes:

text
examples/collection-gap-finder.md

Remote MCP on Cloudflare Workers

This repo can also run as a remote MCP server on Cloudflare Workers. The remote server exposes the same TMDB tools at /mcp over Streamable HTTP, so Claude, Cowork, Claude Desktop connectors, and other remote-MCP clients can connect to a public URL.

The existing local stdio server remains unchanged for Codex and local Claude Desktop use. The Cloudflare entrypoint is src/worker.ts.

The Worker also serves a browser demo at /: Weekend Watch Concierge. It supports solo picks and Watch Party mode, then builds a ranked movie shortlist using TMDB discovery, trending, now-playing, credits, posters, and watch-provider data. The browser app also includes a Help drawer for Cloudflare usage and a Workflow Demos panel with commands for script-first artifacts such as Weekly Streaming Radar, Provider Change Monitor, and Collection Gap Finder.

The browser demo also includes an MCP tool surface panel that calls the deployed /mcp route, verifies the expected tool contract, and samples compare_movies, find_where_to_watch, get_weekend_watchlist, plan_watch_party, build_franchise_watch_order, build_collection_gap_plan, recommend_from_taste_profile, and build_person_watch_path.

Weekend Watch Concierge Workflow Demos panel

Weekend Watch Concierge Watch Party mode

For the complete browser app, deployed Worker, access-token, and MCP handoff, see docs/weekend-watch-concierge.md.

Deploy

  1. Log in to Cloudflare:

    bash
    npx wrangler login
    
  2. Store your TMDB key as a Worker secret:

    bash
    npx wrangler secret put TMDB_API_KEY
    
  3. Store an access token as a Worker secret before sharing the deployment:

    bash
    npx wrangler secret put ACCESS_TOKEN
    

    When ACCESS_TOKEN is set, POST /api/concierge and POST /mcp require:

    text
    Authorization: Bearer <your-access-token>
    
  4. Check the Worker bundle:

    bash
    npm run worker:dry-run
    
  5. Deploy:

    bash
    npm run worker:deploy
    

Cloudflare will print a URL like:

text
https://tmdb-mcp.<your-workers-subdomain>.workers.dev

Use this MCP endpoint in remote clients:

text
https://tmdb-mcp.<your-workers-subdomain>.workers.dev/mcp

Use this browser demo URL:

text
https://tmdb-mcp.<your-workers-subdomain>.workers.dev/

Connect from Claude / Cowork

For Claude custom connectors:

  1. Open Claude settings: Customize -> Connectors.
  2. Click + -> Add custom connector.
  3. Use the deployed Worker MCP URL:
    text
    https://tmdb-mcp.<your-workers-subdomain>.workers.dev/mcp
    
  4. Enable the connector in a conversation and ask a TMDB question, such as:
    text
    What movies are trending this week?
    

For Claude Desktop versions or MCP clients that still require a local command, use the mcp-remote proxy:

json
{
  "mcpServers": {
    "tmdb-remote": {
      "command": "npx",
      "args": [
        "mcp-remote",
        "https://tmdb-mcp.<your-workers-subdomain>.workers.dev/mcp"
      ]
    }
  }
}

Security note

If ACCESS_TOKEN is not configured, the Worker is authless for easy personal testing. Anyone who has the Worker URL can call the read-only TMDB tools and consume your TMDB API quota. Keep ACCESS_TOKEN configured or use Cloudflare Access before sharing this beyond your own accounts.

Weekend Watch Concierge

Run the offline concierge test:

bash
npm test

This builds the TypeScript project, starts a tiny local TMDB-compatible fixture server, and verifies that createWeekendConcierge ranks a requested streaming-service match first while respecting the runtime filter. It does not need a TMDB API key.

Run the Worker locally:

bash
npm run worker:dev

This syncs local values from .env into an untracked .dev.vars file so Wrangler can expose TMDB_API_KEY to the Worker during local development.

For protected local testing, add ACCESS_TOKEN to .env. The browser app has an access-token field and the smoke scripts can read ACCESS_TOKEN or TMDB_MCP_ACCESS_TOKEN from the shell environment.

Open:

text
http://127.0.0.1:8787/

Smoke test the concierge API after the local Worker is running:

bash
npm run smoke:concierge

Smoke test the remote MCP endpoint and call the agent-facing concierge tool:

bash
node scripts/remote-mcp-smoke.mjs http://127.0.0.1:8787/mcp --call-concierge

For a protected deployment:

bash
TMDB_MCP_ACCESS_TOKEN=<your-access-token> node scripts/remote-mcp-smoke.mjs https://tmdb-mcp.<your-workers-subdomain>.workers.dev/mcp --call-concierge

Or test a deployed Worker:

bash
node scripts/concierge-smoke.mjs https://tmdb-mcp.<your-workers-subdomain>.workers.dev

The app uses:

  • POST /api/concierge for ranked movie picks
  • POST /api/collection-gap-plan for Planning Lab collection gaps
  • GET /health for deployment health
  • POST /mcp for remote MCP clients

Agents can call get_weekend_watchlist with:

  • mood: crowd, thriller, thoughtful, funny, family, or mindbend
  • country: watch-provider region, for example IN or US
  • language: original language code, for example en, hi, ta, te, or any
  • runtime: maximum minutes, for example 120, 150, or any
  • minRating: minimum TMDB rating
  • services: preferred streaming services
  • familySafe: set to true to exclude common mature genres when TMDB genre data is available

Agents can call plan_watch_party when the decision is for a group. It accepts:

  • moods: one to three values from crowd, thriller, thoughtful, funny, family, or mindbend
  • groupSize: number of people watching
  • country, language, runtime, minRating, and services: same meaning as the weekend watchlist
  • avoidTitles: titles the group has already seen or wants excluded
  • familySafe: set to true to exclude common mature genres when TMDB genre data is available

Agents can call build_franchise_watch_order for a collection or universe guide. It accepts:

  • query: franchise or collection name, for example The Matrix, Dune, Batman, or Mission Impossible
  • country: watch-provider region, for example IN or US
  • maxMovies: maximum collection entries to include, from 2 to 20

Agents can call build_collection_gap_plan for franchise completion planning. It accepts:

  • query: franchise or collection name
  • watchedTitles: watched titles or TMDB movie IDs
  • country: watch-provider region, for example IN or US
  • services: preferred streaming services
  • maxMovies: maximum collection entries to include, from 2 to 20

Agents can call recommend_from_taste_profile for personalized recommendations. It accepts:

  • likedTitles: one to five movies the user likes
  • dislikedTitles: optional movies the user dislikes or wants to avoid stylistically
  • country, services, language, runtime, and minRating: filters and watch-now preferences
  • maxResults: number of recommendations to return, from 3 to 10

Agents can call build_person_watch_path for an actor, director, writer, or crew member. It accepts:

  • name: person name, for example Keanu Reeves or Christopher Nolan
  • country: watch-provider region, for example IN or US
  • services: preferred streaming services
  • maxTitles: number of watch-path entries to return, from 3 to 8

Cloudflare MCP Demo Workflow

For a concrete end-to-end agent workflow, run the now-playing follow-on demo. It uses the MCP server as a remote client would:

  1. get_now_playing for current theater discovery in a selected region
  2. get_movie_details for the selected title
  3. get_watch_providers for watch-now availability
  4. get_recommendations, with get_similar_movies fallback for very new titles
  5. get_watch_providers for follow-on availability checks

Local stdio MCP:

bash
npm run build
set -a && source ./.env && set +a && npm run demo:now-playing -- --region US

Cloudflare-hosted MCP:

bash
TMDB_MCP_ACCESS_TOKEN=<your-access-token> node scripts/now-playing-follow-on-demo.mjs --mcp-url https://tmdb-mcp.<your-workers-subdomain>.workers.dev/mcp --region US

The script writes the final artifact here:

text
examples/now-playing-follow-on-demo.md

What npm run install:local does

The installer uses the repo-owned launcher at plugins/tmdb/scripts/run-server.sh.

For Codex it:

  • Registers the launcher as an MCP server
  • Installs a local TMDB plugin payload so it appears in the plugin UI

For Claude Desktop it:

  • Registers the same launcher as a local MCP server

It updates:

  • ~/.codex/config.toml
  • ~/.codex/.tmp/plugins/.agents/plugins/marketplace.json
  • ~/.codex/plugins/cache/openai-curated/tmdb/...
  • ~/Library/Application Support/Claude/claude_desktop_config.json

The launcher reads TMDB_API_KEY from your shell environment or from the repo .env file.

Usage with Claude Desktop

If you prefer manual setup, add to ~/Library/Application Support/Claude/claude_desktop_config.json:

json
{
  "mcpServers": {
    "tmdb-local": {
      "command": "/full/path/to/mcp-server-tmdb/plugins/tmdb/scripts/run-server.sh",
      "args": []
    }
  }
}

Restart Claude Desktop after editing the config.

Usage with Codex

The installer adds these blocks to ~/.codex/config.toml:

toml
[mcp_servers.tmdb_local]
command = "/full/path/to/mcp-server-tmdb/plugins/tmdb/scripts/run-server.sh"

[plugins."tmdb@openai-curated"]
enabled = true

Restart Codex after editing the config. In a fresh Codex session, TMDB should appear in the plugin list and contribute the mcp__tmdb__ namespace.

Validation

Offline smoke test:

bash
TMDB_API_KEY=dummy node plugins/tmdb/scripts/smoke-test.mjs

Online smoke test:

bash
set -a && source ./.env && set +a && node plugins/tmdb/scripts/smoke-test.mjs --online

Plugin Docs

For plugin packaging, local install behavior, and Codex-specific notes, see plugins/tmdb/README.md.

Usage with BizClaw / NanoClaw

Built into the agent container. Just set TMDB_API_KEY in your .env file — no configuration needed.

Example Prompts

code
"What's trending in movies this week?"
"Find me Thriller movies from 2023"
"Who is Christopher Nolan and what has he directed?"
"Where can I watch Inception in India?"
"Get details for movie ID 550 (Fight Club)"
"Find movies similar to Interstellar"
"What are the trending TV shows right now?"

License

MIT

常见问题

TMDB Server 是什么?

通过集成 The Movie Database(TMDB)API,提供电影信息查询、搜索能力和个性化推荐。

TMDB Server 提供哪些工具?

提供 3 个工具,包括 search_movies、get_recommendations、get_trending

相关 Skills

Slack动图

by anthropics

Universal
热门

面向Slack的动图制作Skill,内置emoji/消息GIF的尺寸、帧率和色彩约束、校验与优化流程,适合把创意或上传图片快速做成可直接发送的Slack动画。

帮你快速做出适配 Slack 的动图,内置约束规则和校验工具,少踩上传与播放坑,做表情包和演示都更省心。

平台与服务
未扫描137.2k

MCP构建

by anthropics

Universal
热门

聚焦高质量 MCP Server 开发,覆盖协议研究、工具设计、错误处理与传输选型,适合用 FastMCP 或 MCP SDK 对接外部 API、封装服务能力。

想让 LLM 稳定调用外部 API,就用 MCP构建:从 Python 到 Node 都有成熟指引,帮你更快做出高质量 MCP 服务器。

平台与服务
未扫描137.2k

接口测试套件

by alirezarezvani

Universal
热门

扫描 Next.js、Express、FastAPI、Django REST 的 API 路由,自动生成覆盖鉴权、参数校验、错误码、分页、上传与限流场景的 Vitest 或 Pytest 测试套件。

帮你把API与集成测试自动化跑顺,减少回归漏测;能力全面,尤其适合复杂接口场景的QA团队。

平台与服务
未扫描15.4k

相关 MCP Server

Slack 消息

编辑精选

by Anthropic

热门

Slack 是让 AI 助手直接读写你的 Slack 频道和消息的 MCP 服务器。

这个服务器解决了团队协作中需要 AI 实时获取 Slack 信息的痛点,特别适合开发团队让 Claude 帮忙汇总频道讨论或发送通知。不过,它目前只是参考实现,文档有限,不建议在生产环境直接使用——更适合开发者学习 MCP 如何集成第三方服务。

平台与服务
85.9k

by netdata

热门

io.github.netdata/mcp-server 是让 AI 助手实时监控服务器指标和日志的 MCP 服务器。

这个工具解决了运维人员需要手动检查系统状态的痛点,最适合 DevOps 团队让 Claude 自动分析性能数据。不过,它依赖 NetData 的现有部署,如果你没用过这个监控平台,得先花时间配置。

平台与服务
78.9k

by d4vinci

热门

Scrapling MCP Server 是专为现代网页设计的智能爬虫工具,支持绕过 Cloudflare 等反爬机制。

这个工具解决了爬取动态网页和反爬网站时的头疼问题,特别适合需要批量采集电商价格或新闻数据的开发者。不过,它依赖外部浏览器引擎,资源消耗较大,不适合轻量级任务。

平台与服务
51.1k

评论