# MCP Examples > This skill should be used when the user asks for "MCP examples", "real-world patterns", "code search patterns", "browser proxy patterns", "process management patterns", "show me examples", or wants to see actual implementations from lci, agnt, or other real MCPs. Use when this capability is needed. - Skill: `tomevault-io/mcp-examples` (Agent Skill, multi-file: 2 files) - Install (CLI): `npx skillmds@latest add tomevault-io/mcp-examples` - Raw SKILL.md: https://api.skillmd.com/api/skills/tomevault-io/mcp-examples/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: AI & ML - Author: tomevault-io (https://skillmd.com/u/tomevault-io) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/tomevault-io/mcp-examples --- # MCP Examples ## Purpose Provide real-world MCP patterns from production servers: code search (lci), browser integration (agnt), process management, and knowledge bases. ## When to Use - Need concrete examples of patterns - Want to see actual implementations - Designing similar functionality - Learning from working systems ## Code Search Pattern (lci) ### Architecture - **Pattern:** Hub-and-Spoke + Progressive Discovery - **Tools:** 8+ tools - **Token System:** result_id, symbol_id ### Key Tools **search - Hub tool** ```json { "input": {"pattern": "string", "filter": "optional"}, "output": { "results": [ {"id": "r1", "name": "User.authenticate", "preview": "...", "conf": 0.95} ], "has_more": true, "total": 127 } } ``` **get_definition - Spoke tool** ```json { "input": {"id": "r1"}, "output": { "symbol_id": "s1", "name": "User.authenticate", "signature": "...", "source": "...", "location": {"file": "user.ts", "line": 42} } } ``` **Token efficiency:** ID reference saves ~80% tokens vs. repeating full code ### Progressive Detail Example ``` Query: "authenticate" High match (0.95): Full details (200 tokens) - Name, signature, docs, preview, location Medium match (0.70): Summary (50 tokens) - Name, type, file Low match (0.40): Minimal (10 tokens) - Name, ID only ``` ## Browser Proxy Pattern (agnt) ### Architecture - **Pattern:** CRUD + Aggregation - **Tools:** 10+ tools - **Token Systems:** proxy_id, session_id, request_id ### Key Tools **proxy_start - Create** ```json { "input": {"target_url": "http://localhost:3000"}, "output": { "proxy_id": "dev", "listen_addr": "http://localhost:12345", "status": "running" } } ``` **currentpage - Aggregation** ```json { "input": {"proxy_id": "dev"}, "output": { "session_id": "page-1", "url": "http://localhost:3000", "errors_count": 3, // Not full error objects "interactions_count": 127, // Not every interaction "mutations_count": 45, // Not every mutation "performance": {...} }, "detail_access": "Use detail=['errors'] for full data" } ``` **Key pattern:** Counts in overview, full data on request ### Hierarchical IDs ``` proxy_id (dev) ↓ session_id (page-1) ↓ request_id (req_a1b2) ``` Each level provides more specificity. ## Process Management Pattern ### Architecture - **Pattern:** CRUD + Lazy Loading - **Tools:** 8+ tools - **Token System:** process_id ### Progressive Status **Level 1 - Count** ```json { "active": 5, "stopped": 2 } ``` **Level 2 - List** ```json { "processes": [ {"id": "p1", "name": "dev-server", "status": "running"}, {"id": "p2", "name": "test", "status": "running"} ] } ``` **Level 3 - Status** ```json { "id": "p1", "status": "running", "uptime": "2h15m", "memory": "245MB", "preview": "Server listening :3000" } ``` **Level 4 - Full** ```json { /* ...all Level 3... */, "full_output": "... complete logs ...", "env": {...}, "metrics": {...} } ``` ## Knowledge Base Pattern ### Architecture - **Pattern:** Discovery-Detail - **Tools:** Search, topics, articles - **Token System:** article_id, topic_id ### Layered Access ``` list_topics() → ["auth", "deploy", "monitor"] get_topic_summary("auth") → {articles: 12, updated: "2024-01"} search_articles("OAuth") → [{id: "a1", title: "...", preview: "..."}] get_article("a1") → {title, content, related: [...]} ``` ## Common Patterns Across Examples ### 1. ID Reference System All use IDs to avoid repeating data: - **lci:** result_id → symbol_id - **agnt:** proxy_id → session_id → request_id - **process:** process_id - **kb:** topic_id → article_id **Savings:** 70-90% token reduction ### 2. Progressive Detail All vary detail by context: - **lci:** By confidence (0.95 = full, 0.40 = minimal) - **agnt:** By request (counts vs. full arrays) - **process:** By depth (count → list → status → full) - **kb:** By layer (topics → summary → full article) ### 3. Automation Flags All include standard flags: ```json { "has_more": boolean, "total": integer, "returned": integer, "complete": boolean } ``` ### 4. Accept Extra Parameters All accept unknown params with warnings: ```typescript const {known, params, ...extra} = input if (extra) warnings.push(`Unknown: ${Object.keys(extra)}`) ``` ## Anti-Patterns Seen and Fixed ### ❌ Repeating Data **Before (wasteful):** ```json // Tool 1 {"results": [{"name": "...", "code": "... 200 lines ..."}]} // Tool 2 needs same data // User copies entire result ``` **After (efficient):** ```json // Tool 1 {"results": [{"id": "r1", "name": "...", "preview": "10 lines"}]} // Tool 2 input: {"id": "r1"} // Reference only ``` ### ❌ No Progressive Detail **Before:** ```json { "results": [ {"name": "...", "full": "... 500 tokens ..."}, {"name": "...", "full": "... 500 tokens ..."}, {"name": "...", "full": "... 500 tokens ..."} ] } ``` **After:** ```json { "results": [ {"id": "a1", "conf": 0.95, "full": "..."}, // Only high confidence {"id": "b2", "conf": 0.70, "summary": "..."}, {"id": "c3", "conf": 0.40} // Just ID ] } ``` ### ❌ Flat Structure **Before (15+ tools, no organization):** ``` search_users, search_posts, get_user, get_post, ... ``` **After (grouped):** ``` Query Tools: search Lookup Tools: get_user, get_post Management: create_user, update_user ``` ## Real-World Token Savings ### lci code_search Tool **Without IDs:** - Average result: 250 tokens (full code) - 10 results: 2,500 tokens **With IDs:** - Average preview: 50 tokens - 10 results: 500 tokens - **Savings:** 80% ### agnt currentpage Tool **Without aggregation:** - Full errors array: 400 tokens - Full interactions: 600 tokens - Full mutations: 300 tokens - **Total:** 1,300 tokens **With aggregation:** - Error count: 10 tokens - Interaction count: 10 tokens - Mutation count: 10 tokens - **Total:** 30 tokens (97% savings) - Use detail parameter for full arrays when needed ## Quick Reference **Proven patterns:** 1. **Hub-and-Spoke** - lci (search → details) 2. **CRUD** - agnt (lifecycle management) 3. **Aggregation** - agnt currentpage (counts not arrays) 4. **Lazy Loading** - process status (overview → full) 5. **Discovery-Detail** - kb (topics → articles) **Key lessons:** - IDs save 70-90% tokens - Progressive detail by relevance/confidence - Counts in overview, arrays on request - Accept extra params with warnings - Automation flags for AI agents Study these real-world examples when designing similar functionality. --- > Converted and distributed by [TomeVault](https://tomevault.io/claim/standardbeagle) — claim your Tome and manage your conversions.