MCP Server v1

Ask questions about India's geo data in natural language. The bharatlas MCP server connects LLMs (Claude, GPT, Gemini, Cursor, etc.) to curated geo layers plus community submissions.

Install

Works with any LLM client that supports MCP: Claude, GPT, Gemini, Llama, Mistral, or local models via Cursor, Continue, Cline, Windsurf, etc.

{
  "mcpServers": {
    "bharatlas": {
      "command": "npx",
      "args": ["-y", "bharatlas-mcp"]
    }
  }
}

# Claude Code
.mcp.json (project root) or ~/.claude.json

# Claude Desktop
~/Library/Application Support/Claude/claude_desktop_config.json

# Cursor
~/.cursor/mcp.json

# Windsurf
~/.codeium/windsurf/mcp_config.json

# VS Code (Copilot / Continue / Cline)
.vscode/mcp.json (project) or settings.json

Developers: test tools without an LLM via npx @modelcontextprotocol/inspector npx bharatlas-mcp

What you can ask

Counting and filtering

How many national parks vs wildlife sanctuaries in India?

101 national parks, 560 sanctuaries (from the gs_wildlife layer, grouped by category)

How many villages are in Bengaluru Urban district?

949 villages (lgd_villages filtered by dtname=BENGALURU URBAN)

How many health facilities are in Bihar?

8,363 facilities: 3,232 sub-centres, 591 PHCs, 74 CHCs (nic_health filtered by state)

How many wards does Chennai have vs Pune?

Chennai: 200, Pune: 58 (from wards_chennai and wards_pune layer metadata)

Location queries

What state, district, and seismic zone is Bengaluru in?

Karnataka, Bengaluru Urban, Seismic Zone II (locate endpoint checks 12 layers in one call)

Which blocks are in district 571?

10 blocks: Kunigal, Tumakuru, Gubbi, Turuvekere, Tiptur... (lgd_blocks filtered by dtcode11)

Cross-layer queries

How many airports in Bengaluru district? What are their types?

3 airports: HAL (Domestic), Yelahanka AFB (Civil Enclave), Kempegowda International. The MCP locates the district, then filters the airports layer by state and district.

Which airports in Karnataka are near water bodies?

Hubballi Airport (~3 km from Unkal Lake), Mangalore Airport (between Netravathi and Gurupura rivers), Jindal Vijaynagar (~7 km from JSW Reservoir). Cross-references airports + reservoirs layers.

Spatial queries (multi-step)

Which villages in Madhya Pradesh are in eco-sensitive zones?

MP has 4 eco-sensitive zones (Kharmor, Chambal, Orchha, Kheoni). The MCP narrows 47,571 MP villages by district, then tests each against the eco-zone boundaries.

Which districts does NH-44 pass through?

Delhi, UP, MP, Telangana, Karnataka. The MCP samples points along the route and locates the state at each point.

How many hospitals are in flood-prone areas of Assam?

3,909 health facilities in Assam (narrowed by state). For precise flood-zone overlap, the MCP tests hospital points against the India Flood Inventory layer.

8 tools

• list_layers -- discover layers by category, level, source, or text search
• get_layer_schema -- column names, types, distinct values (call before querying)
• query_layer -- filter, select, group by any column; results include _lat/_lng for spatial layers
• locate -- point-in-polygon across all admin layers + zones at once
• nearby -- find features within a radius (works for points, polygons, and lines)
• get_layer_detail -- download URLs in 5 formats (parquet, pmtiles, geojson, kml, shapefile)
• list_categories -- browse by category with layer counts
• list_submissions -- community-contributed layers under open licenses

How it works

The MCP server is a thin wrapper over the bharatlas REST API. It translates LLM tool calls into API requests and returns structured JSON. No API key needed. All data is read-only and openly licensed.

The server sends instructions to the LLM at connection time that teach it:

• Schema-first pattern (check column names before querying)
• Source preference (LGD for admin boundaries, multiple sources for wards)
• Spatial join workflow (locate for context, query for data, combine)
• Concept-to-layer mapping ("water bodies" = rivers + reservoirs + wetlands + ramsar)

Data

Curated layers across multiple categories: admin boundaries (state to village), city wards, forests, wildlife, eco-zones, rivers, reservoirs, dams, seismic zones, floods, highways, airports, health facilities, pincodes, electoral constituencies. Plus community submissions.

Sources: LGD, SOI, Bhuvan, OpenCity, DataMeet, PMGSY, GatiShakti, Bharatmaps, bharatviz, CWC, data.gov.in. All open-licensed.

Links

• npm: bharatlas-mcp
• REST API reference
• GitHub source