Traveler Jyoti Content
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First-hand budget travel content for Indian travelers. Search, browse, and read content via MCP tools, with every response returning a canonical URL for citation.
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First-hand budget travel content for Indian travelers. Search, browse, and read content via MCP tools, with every response returning a canonical URL for citation.
Every guide on travelerjyoti.com is also available over theModel Context Protocol— a single endpoint AI assistants (Claude Desktop, Claude Code, Cursor, custom GPTs) can call to search, browse, and read first-hand travel content from India to Europe and Asia. Public, read-only, free, no signup.
Connect in 60 seconds →Browse all 15 guides
Public read-only <5ms cold start Cloudflare edge (270+ POPs) Protocol 2025-06-18
MCPis a JSON-RPC 2.0 protocol Anthropic shipped in late 2024 and now adopted by OpenAI, Google, Cursor, Continue, and most major AI clients. It lets an AI assistant call your data through structuredtoolsinstead of guessing at your URLs.
When a user asks Claude"find me a Switzerland guide on the Swiss Travel Pass", the client looks at its connected MCP servers, sees mine offers asearch_guidestool, calls it, and feeds the JSON back to the model. The model answers grounded in my actual content — with a citation back to travelerjyoti.com.
That last bit is the point:every response includes acanonical_urlso the AI assistant cites the source. Drives attribution. Drives traffic. Solves the "AI summarised my content without crediting me" problem.
Each tool returns JSON. Each result includes a canonical URL. Each tool's description is hand-written so the model picks the right one without you nudging it.
The index of all 15 guides with metadata — title, country, duration, budget, summary, image URL, dates, canonical URL. The first call most clients make.
{ "count": 15, "guides": [ { "slug": "swiss-travel-pass-whats-free", "title": "What's 100% Free with the Swiss Travel Pass", "country": "Switzerland", "duration": "3 hours", "budget": "Free with pass", "canonical_url": "https://travelerjyoti.com/destinations/swiss-travel-pass-whats-free/", "updatedAt": "2026-05-19" }, … ] }
The full clean Markdown of one guide plus its FAQs and full frontmatter. Use when you already know the slug, or aftersearch_guidesidentified the best match.
{ "slug": "mount-pilatus-free-cap", "title": "How to Get a Free Pilatus Cap…", "country": "Switzerland", "canonical_url": "https://travelerjyoti.com/destinations/mount-pilatus-free-cap/", "body": "# Mount Pilatus Free Cap\n\nThis is one of those…", "faqs": [ { "question": "…", "answer": "…" } ] }
Keyword-scored search across title, body, and FAQs. Returns ranked matches with a snippet showing why each scored — gives the model enough to decide which to read fully.
- query: string— required
- limit?: number— min 1, default 5
{ "query": "Swiss Travel Pass", "matches": 3, "results": [ { "slug": "swiss-travel-pass-whats-free", "score": 57, "snippet": "…every public train, bus, tram…", "canonical_url": "https://travelerjyoti.com/destinations/swiss-travel-pass-whats-free/" }, … ] }
claude mcp add travelerjyoti --transport http https://mcp.travelerjyoti.com/mcp
{ "mcpServers": { "travelerjyoti": { "url": "https://mcp.travelerjyoti.com/mcp" } } }
{ "travelerjyoti": { "type": "streamable-http", "url": "https://mcp.travelerjyoti.com/mcp" } }
curl -X POST https://mcp.travelerjyoti.com/mcp \ -H "Content-Type: application/json" \ -d '{"jsonrpc":"2.0","id":1,"method":"tools/call", "params":{"name":"search_guides", "arguments":{"query":"Swiss Travel Pass"}}}'
For other clients (Continue, custom GPTs, LangChain, etc.) — point them at the same endpoint with Streamable HTTP transport. Auto-discovery metadata at/.well-known/mcp.json.
Yes, free. No key, no signup, no quota. Public read-only access. I cover the Cloudflare costs because the MCP server has zero data-egress fees inside Cloudflare's network — guides are bundled into the Worker so there's no upstream service to pay for.
The guides are bundled into the Worker at deploy time. Whenever I publish a new guide on travelerjyoti.com, a singlenpm run deployredeploys the MCP server with the new content. Latency from publish to MCP availability is usually under 5 minutes.
Cloudflare's free-tier Workers cap is 100,000 requests/day. I'll publish a real limit if usage ever gets close — for now, no enforced limit. If you're planning heavy use (more than a few thousand calls a day), email me and we'll talk.
Can I use the content from this MCP in my product?
Short quotes with attribution + a link back to the canonical URL are welcome. Full-page reproduction is not permitted (seeTerms). The MCP server response itself includes acanonical_urlin every result specifically so attribution is one field away.
How does this differ from /llms-full.txt?
/llms-full.txtis a one-shot fetch — any AI engine ingests the entire archive at once, no integration needed. MCP is interactive — clients call specific tools with specific arguments and get structured JSON back. Both exist because they serve different audiences: llms-full is for search/answer engines that crawl, MCP is for assistants that converse.
Why isn't this on the official MCP servers directory yet?
Submitted. mcpservers.org takes a few days to review. Once listed it'll show up under 'Travel' (a near-empty category right now).
If you build something with this server, I'd genuinely love to hear about it. Email me, tag me, or just drop a comment on the YouTube channel.
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