lampa-mcp-server
MCP server for AI-assisted development on the Lampa open-source TV app, providing read-only access to the source tree with 41 tools and 5 resources for structured analysis, planning, editing, and validation.
README
lampa-mcp-server
An MCP server for AI-assisted development on the Lampa open-source TV app.
It gives AI agents (Claude, Cursor, etc.) structured, read-only access to the Lampa source tree — so they understand the repo before making changes.
What it does
The server exposes 57 tools and 6 resources across nine capability layers:
| Layer | File | Tools | Purpose |
|---|---|---|---|
| Discovery | discovery.ts |
6 | Navigate repo structure, list modules, search code, read files |
| Analysis | analysis.ts |
7 | Locate settings, API calls, UI components, translations, dependency maps |
| Planning | planning.ts |
4 | Generate change plans, impact analysis, edit targets, risk scans |
| Editing | editing.ts |
4 | Draft patches, scaffold plugins, generate hook/setting boilerplate |
| Validation | validation.ts |
4 | Quality checks, find tests, resolve build commands, query docs |
| Lampa Deep | lampa_deep.ts |
8 | Deep Lampa-specific analysis: providers, events, translations, lifecycle |
| Advanced | advanced.ts |
8 | File reads, storage schema, event bus map, network map, pattern guide |
| Lampa Modern | lampa_modern.ts |
10 | Maker modules, CUB API (Lampa subset), WebSocket, components, settings, packaging |
| CUB API | cub.ts |
6 | Full CUB API surface from Lampa source: catalog, auth, sync, data models |
Tools
Discovery
repo_overview— summarise app structure, folders, entrypoints, plugins, and scriptslist_modules— list JS/TS modules in any subfolderfind_files— find files by name pattern or extensionsearch_code— regex/text search with file:line previews (usesripgrepwhen available)read_file_segment— read a specific line range from any repo filelist_scripts— show all NPM scripts frompackage.json
Analysis
find_settings— locateLampa.Settings.addandLampa.Storageusage; optionally filter by keywordfind_api_calls— findfetch,$.ajax, and provider integrationsfind_ui_component— find templates, components, and views by namefind_translation_keys— look up translation key definitions and usages across all language filesfind_styles_for_module— find CSS/SCSS files related to a module or feature namemodule_dependency_map— map imports and reverse dependencies with change blast radiusfind_feature— infer all files relevant to a named feature (player, catalog, iptv, search, etc.)
Planning
plan_feature_change— step-by-step implementation plan (call beforedraft_patch)impact_analysis— reference count and risk level for a target filesuggest_edit_targets— minimal file set and safe insertion guidance for a feature requestrisk_scan— detect coupling risks: global events, storage, shared templates, DOM globals
Editing
draft_patch— guided patch draft with file previews and Lampa patterns (requires priorplan_feature_change)insert_hook— find the bestLampa.Listenerhook point for a lifecycle triggeradd_setting— generate toggle / select / input setting boilerplate with storage wiringscaffold_plugin_integration— full plugin folder scaffold withmain.js, CSS, and component boilerplate
Validation
run_grep_checks— scan for TODOs,console.logleftovers, looseundefinedchecks, hardcoded stringslist_related_tests— find spec files related to a module or featurerun_build_hint— resolve the right build / dev / test / lint command frompackage.jsondoc_lookup— search generated docs or README for a topic
Lampa Deep
plugin_deep_dive— single-call analysis of a plugin folder: files, Lampa API usage, events, settings, entry-point previewlist_streaming_providers— catalog all online streaming providers with base URLs, methods, and Lampa APIs usedtranslation_coverage— compare all language files against the English reference; shows coverage % and missing keys per languagetrace_event— trace aLampa.Listenerevent through the full codebase: who sends it, who follows itlampa_api_surface— extract the completeLampa.*global API surface: every module with sub-methods and file usage countslist_templates— list all UI templates insrc/templates/; optionally read one to inspect HTML and data bindingsgenerate_plugin_boilerplate— generate working plugin code for selected features: settings, hooks, storage, lang keys, IPTVcomponent_lifecycle— deep-analyse a component: lifecycle methods, events, APIs, storage, templates, and settings
Advanced
read_file— read a complete file (truncated atmax_lines); useread_file_segmentfor large filesget_storage_schema— scan allLampa.Storage.get/setcalls; returns a complete key → default / readers / writers tablelist_all_events— build a fullLampa.Listenerevent bus map: every event, listener count, emitter count, orphan detectionget_network_map— extract all hardcoded URLs, base URL variables, and proxy names from any scopevalidate_plugin— score a plugin against 10 Lampa conventions (IIFE, strict mode,appreadybootstrap, noeval, etc.)extract_template_html— extract actual HTML markup, CSS classes, and data-binding placeholders fromsrc/templates/*.jsget_core_module— browse and readsrc/core/modules; lists all available when called without a nameexplain_lampa_pattern— pattern reference guide backed by live source examples:iife-plugin,storage,settings,events,component,request,template,activity,player-hook
Lampa Modern (v3.0 architecture)
maker_module_map— map Maker classes (Card, Main, Category, Line, …), module/map files, and lifecycle hookscub_api_catalog— catalog all CUB cloud REST endpoints with method and source filesocket_protocol_map— WebSocket inbound/outbound methods, mirrors, and payload envelopeactivity_component_registry— allComponent.addregistrations and Router routeslampa_settings_flags—window.lampa_settingsfeature flags and platform overridesplatform_packaging_guide— gulp targets for web, webOS, Tizen, GitHub Pages, plugins, docscontent_rows_api— allContentRows.addhome-screen injection pointsfavorite_category_schema— favorite/bookmark category types and timeline marksmanifest_mirrors_map— cub_mirrors, soc_mirrors, cub_domain resolution logicupgrade_migration_checker— detect deprecated 2.x APIs (Lampa.Card, InteractionMain, etc.) in a file
CUB API (from Lampa source — CUB developer docs)
cub_api_catalog— full CUB API catalog extracted from Lampa (account, bookmarks, timeline, AI, collections, TMDB proxy, plugins, WebSocket)cub_endpoint_detail— single endpoint with source file, code context, feature gatescub_auth_guide— device/add login, token/profile headers, Permit gating, Premium, mirrorscub_data_models— bookmark types, timeline storage, favorite categories, sync shapescub_sync_guide— bookmark/timeline/storage sync: REST dump/changelog + WebSocketcub_timeline_hash_guide— Utils.hash() algorithm for watch progress keys
Resources
| URI | Description |
|---|---|
repo://overview |
Top-level directory listing |
repo://scripts |
NPM scripts as JSON |
docs://index |
Generated JSDoc (requires npm run doc in the Lampa repo) |
settings://catalog |
All Lampa.Settings.add registrations in the repo |
api://integrations |
All API and network call sites |
cub://lampa-api |
CUB API endpoints JSON extracted from Lampa source |
Requirements
- Node.js 20+
- A local checkout of the Lampa source repo
- Optional:
ripgrep(rg) for faster search — falls back to pure Node if not present
Setup
git clone https://github.com/your-username/lampa-mcp-server
cd lampa-mcp-server
npm install
npm run build
Set the path to your Lampa checkout via the environment variable:
export LAMPA_REPO_PATH=/path/to/lampa-source
Or pass it inline when starting the server:
LAMPA_REPO_PATH=/path/to/lampa-source node dist/index.js
Connect to Claude Desktop
Add to ~/Library/Application Support/Claude/claude_desktop_config.json:
{
"mcpServers": {
"lampa-mcp-server": {
"command": "node",
"args": ["/absolute/path/to/lampa-mcp-server/dist/index.js"],
"env": {
"LAMPA_REPO_PATH": "/absolute/path/to/lampa-source"
}
}
}
}
Connect to Cursor
Add to .cursor/mcp.json in your project (or the global ~/.cursor/mcp.json):
{
"mcpServers": {
"lampa-mcp-server": {
"command": "node",
"args": ["/absolute/path/to/lampa-mcp-server/dist/index.js"],
"env": {
"LAMPA_REPO_PATH": "/absolute/path/to/lampa-source"
}
}
}
}
Recommended agent workflow
The server enforces a deliberate two-step contract: plan first, patch second.
repo_overview → find_feature → module_dependency_map
→ plan_feature_change → draft_patch
For deep plugin work, start with the single-call analysis tools:
plugin_deep_dive → maker_module_map → cub_api_catalog
→ plan_feature_change → draft_patch → validate_plugin
For CUB account/sync work:
cub_auth_guide → cub_api_catalog → cub_sync_guide
→ cub_data_models → cub_endpoint_detail
System prompt for best results:
You are an AI coding agent working on the Lampa source repository. Always begin by collecting context through MCP tools: overview, relevant modules, settings, API calls, and dependency map. Do not invent project structure or framework patterns. Before writing code, produce: affected files, why each matters, implementation steps, risks, and validation checks. When generating code, preserve naming, style, and surrounding patterns used in the target files.
Project structure
src/
├── index.ts # Server entry point
├── config.ts # LAMPA_REPO_PATH + CUBCTL_PATH config
├── utils/
│ ├── fs.ts # File system helpers
│ ├── search.ts # ripgrep + Node fallback search
│ ├── lampa.ts # Lampa-specific patterns, feature map, risk patterns
│ ├── lampa_deep.ts # Deep analysis utilities (events, lifecycle, providers)
│ ├── lampa_modern.ts # Lampa 3.0 architecture extractors (Maker, CUB subset, socket)
│ └── cub.ts # CUB API extraction from Lampa source (scanner + metadata)
├── tools/
│ ├── discovery.ts # Phase 1 — repo navigation (6 tools)
│ ├── analysis.ts # Phase 2 — Lampa understanding (7 tools)
│ ├── planning.ts # Phase 3 — change planning (4 tools)
│ ├── editing.ts # Phase 4 — assisted editing (4 tools)
│ ├── validation.ts # Phase 5 — quality checks (4 tools)
│ ├── lampa_deep.ts # Lampa-specific deep analysis (8 tools)
│ ├── advanced.ts # File I/O, schema, pattern guide (8 tools)
│ ├── lampa_modern.ts # Lampa 3.0 architecture tools (10 tools)
│ └── cub.ts # CUB API extraction from Lampa source (6 tools)
└── resources/
└── index.ts # MCP resources (6 read-only stable context endpoints)
Development
npm run build # compile TypeScript → dist/
npm run dev # run directly with ts-node
npm start # run compiled dist/index.js
npm run typecheck # type-check without emitting
npm run lint # ESLint
npm run lint:fix # ESLint with auto-fix
npm run format # Prettier write
npm run format:check # Prettier check (CI)
License
MIT
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.