explainx.ainewsletter3.4k
other

TV Show Recommender (TMDb)▌

terryso

by terryso

Discover the best ever TV series with our TV Show Recommender. Get personalized picks, trends, and streaming info from T

Integrates with The Movie Database (TMDb) API to provide TV show discovery, recommendations, and streaming information based on genres, trends, and viewer preferences.

github stars

★ 5

GitHubnpm
0 commentsdiscussion

Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.

10 specialized TV discovery toolsReal-time streaming provider informationActor-based show discovery

best for

  • / TV show enthusiasts looking for recommendations
  • / Finding what to watch next based on preferences
  • / Checking streaming availability before watching
  • / Exploring actor filmographies and credits

capabilities

  • / Get TV show recommendations by genre
  • / Find similar shows to ones you like
  • / Search shows by actor or celebrity
  • / Check streaming availability and watch providers
  • / Get detailed show information and reviews
  • / Discover trending and popular shows

what it does

Connects to The Movie Database (TMDb) API to help you discover TV shows through natural language queries. Get recommendations by genre, find similar shows, check where to watch, and explore actor filmographies.

about

TV Show Recommender (TMDb) is a community-built MCP server published by terryso that provides AI assistants with tools and capabilities via the Model Context Protocol. Discover the best ever TV series with our TV Show Recommender. Get personalized picks, trends, and streaming info from T It is categorized under other. This server exposes 12 tools that AI clients can invoke during conversations and coding sessions.

how to install

You can install TV Show Recommender (TMDb) in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.

license

MIT

TV Show Recommender (TMDb) is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

README content is unavailable from source data for this server.

Open GitHub repository

FAQ

What is the TV Show Recommender (TMDb) MCP server?
TV Show Recommender (TMDb) is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
How do MCP servers relate to agent skills?
Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
How are reviews shown for TV Show Recommender (TMDb)?
This profile displays 37 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.7 out of 5—verify behavior in your own environment before production use.

Use Cases▌

Extended AI Capabilities

Add new capabilities to Claude beyond text generation

Example

Access external data sources, execute code, interact with tools and services

✓

Transform Claude from chatbot to action-taking agent

Context Enhancement

Provide Claude with access to relevant context and data

Example

Load project documentation, access knowledge bases, query databases

✓

Get more accurate, context-aware responses

Workflow Automation

Automate multi-step workflows combining AI and external tools

Example

Research → Summarize → Create document → Send notification

✓

Complete complex tasks end-to-end without manual steps

Implementation Guide▌

Prerequisites

  • ›Claude Desktop 0.7.0+ or Cursor IDE with MCP support
  • ›Basic understanding of MCP architecture and capabilities
  • ›Access credentials for integrated services (if required)
  • ›Willingness to experiment and iterate on configuration

Time Estimate

15-60 minutes depending on server complexity

Installation Steps

  1. 1.Install MCP server: npm install -g [package-name] or via GitHub
  2. 2.Add server configuration to ~/.claude/mcp.json
  3. 3.Provide required credentials and configuration
  4. 4.Restart Claude Desktop to load new server
  5. 5.Test basic functionality with simple prompts
  6. 6.Explore capabilities and experiment with use cases
  7. 7.Document successful patterns for reuse

Troubleshooting

  • ⚠MCP server not loading: Check config syntax, verify installation
  • ⚠Connection errors: Check network, firewall, credentials
  • ⚠Feature not working: Read server docs, check required parameters
  • ⚠Performance issues: Monitor resource usage, check for network latency
  • ⚠Conflicts with other servers: Check port assignments, namespace collisions

Best Practices▌

✓ Do

  • +Read server documentation thoroughly before setup
  • +Start with simple use cases to validate functionality
  • +Test in non-production environment first
  • +Monitor resource usage and performance
  • +Keep servers updated for bug fixes and new features
  • +Document configuration for team members
  • +Use environment variables for sensitive configuration

✗ Don't

  • −Don't grant overly permissive access to MCP servers
  • −Don't skip reading security considerations in docs
  • −Don't expose sensitive data without proper controls
  • −Don't run untrusted MCP servers without code review
  • −Don't ignore error messages—investigate root cause

💡 Pro Tips

  • ★Combine multiple MCP servers for powerful workflows
  • ★Create custom MCP servers for your specific needs
  • ★Share successful configurations with team
  • ★Use MCP inspector for debugging
  • ★Join MCP community for tips and troubleshooting

Technical Details▌

Architecture

Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.

Protocols

  • Model Context Protocol (MCP)
  • JSON-RPC 2.0
  • stdio or HTTP transport

Compatibility

  • Claude Desktop
  • Cursor IDE
  • Custom MCP clients

When to Use This▌

✓ Use When

Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.

✗ Avoid When

Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.

Integration▌

  • →Tool composition: Chain multiple MCP tools in workflows
  • →Context augmentation: Provide AI with relevant external data
  • →Action delegation: Let AI execute tasks on external systems
  • →Bidirectional sync: Keep AI context and external systems in sync

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.

List & Promote Your MCP Server

Share your MCP server with the developer community

GET_STARTED →
MCP server reviews

Ratings

4.7★★★★★37 reviews
  • ★★★★★Pratham Ware· Dec 24, 2024

    TV Show Recommender (TMDb) is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.

  • ★★★★★Sofia Yang· Dec 24, 2024

    I recommend TV Show Recommender (TMDb) for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • ★★★★★Michael Gupta· Nov 15, 2024

    According to our notes, TV Show Recommender (TMDb) benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • ★★★★★Olivia Smith· Oct 6, 2024

    TV Show Recommender (TMDb) has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • ★★★★★Isabella Sharma· Sep 25, 2024

    TV Show Recommender (TMDb) is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.

  • ★★★★★Alexander Garcia· Sep 25, 2024

    TV Show Recommender (TMDb) is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • ★★★★★Sakshi Patil· Sep 21, 2024

    TV Show Recommender (TMDb) is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • ★★★★★Sofia Chen· Sep 9, 2024

    According to our notes, TV Show Recommender (TMDb) benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • ★★★★★Ira Chawla· Aug 16, 2024

    We wired TV Show Recommender (TMDb) into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

  • ★★★★★Alexander Sethi· Aug 16, 2024

    We evaluated TV Show Recommender (TMDb) against two servers with overlapping tools; this profile had the clearer scope statement.

showing 1-10 of 37

1 / 4