mcpbeat

Atlasemoji MCP Server

com.atlasemoji/mcp
answering

Atlasemoji is answering right now. Last checked 12 min ago. It exposes 17 tools.

AI-ready GIS, geofencing, DataSynch, CRM, inventory, routing, APIs, telemetry and workflows.

Uptime history 42 hours of history
42 hours agonow
100.0%
Uptime 24h
91 of 91 checks
17
Tools
read from the server
330 ms
Response time
average over 24h
open, no key
Access
streamable-http

Connect this server

Endpoint below is the one we actually reach during checks — not the one copied from a README. Last verified 12 min ago.

run in your terminal
claude mcp add mcp --transport http https://atlasemoji.com/api/mcp
~/Library/Application Support/Claude/claude_desktop_config.json
{
  "mcpServers": {
    "mcp": {
      "url": "https://atlasemoji.com/api/mcp"
    }
  }
}
~/.codex/config.toml
[mcp_servers.mcp]
url = "https://atlasemoji.com/api/mcp"
.cursor/mcp.json
{
  "mcpServers": {
    "mcp": {
      "url": "https://atlasemoji.com/api/mcp"
    }
  }
}
.vscode/mcp.json
{
  "mcpServers": {
    "mcp": {
      "url": "https://atlasemoji.com/api/mcp"
    }
  }
}

Available tools 17

Read directly from the server with tools/list, grouped by what they act on. If a tool disappears, we record the date.

validate
validate_coordinates
Prepare latitude and longitude values for Atlasemoji maps, routes, geofences, telemetry, mobile events, customer locations, assets, vessels, aircraft, storytelling, and operational workflows by checking accepted geographic ranges and returning normalized coordinates.
validate_geojson
Prepare GeoJSON features, collections, points, lines, polygons, and geometry collections for Atlasemoji maps, routes, service areas, stories, manifests, geofences, learning exercises, APIs, and location-aware workflows by checking their basic structure.
validate_manifest_schema
Prepare geographic and operational manifest data for Atlasemoji use. Checks the supplied manifest structure, durable identity, locations, addresses, and coordinates before the data is used with workspaces, routes, storytelling, geofencing, DataSynch, inventory, CRM, or other Atlasemoji workflows.
wanderloop
wanderloop.get_manifest
Retrieve a previously saved Wanderloop topic or place-research manifest by manifest ID, including its normalized provider evidence, statuses, map data, citations, and source links when available.
wanderloop.list_provider_capabilities
List every registered Wanderloop source integration without dropping unavailable or unconfigured providers. Returns provider identity, current topic assignment, execution mode, and required environment configuration so an agent can understand which historical, academic, archival, environmental, and natural-history sources Atlasemoji can invoke.
wanderloop.research_place
Assemble a cited, geographically grounded Wanderloop research package for a location. Queries Atlasemoji-approved historical, archival, academic, environmental, wildlife, and place-record providers through the same provider registry used by the Wanderloop application. Returns evidence records, provider execution status, citations, GeoJSON map features, and saved manifest links. This is evidence assembly, not an unsupported AI-written story.
detect
detect_file_schema
Analyze a bounded preview of CSV, spreadsheet, JSON, EDI-normalized, EDIFACT-normalized, cXML-derived, inventory, telemetry, CRM, item, location, shipment, or partner records to identify their structure and determine how they may fit Atlas DataSynch workflows.
detect_location_columns
Identify address, city, state, province, region, postal code, latitude, and longitude fields in supplied business or operational records so they can be connected to Atlasemoji locations, customer sites, facilities, routes, territories, inventory, telemetry, geofences, and DataSynch workflows.
preview
preview_datasynch_rows
Review a bounded preview of partner, customer, ERP, WMS, TMS, CRM, inventory, telemetry, location, API, spreadsheet, EDI-normalized, EDIFACT-normalized, or cXML-derived records in the context of an authorized Atlasemoji company, workspace, or manifest.
preview_geofence
Prepare a radius-based geofence for an Atlasemoji location-aware workflow. Helps agents and users evaluate the proposed center, radius, coverage area, label, and tenant context before using production geofencing for movement, scans, arrivals, exits, dwell, proximity, telemetry, alerts, or downstream actions.
capabilities
list_capabilities
Discover how Atlasemoji supports Atlas DataSynch, GIS, geofencing, CRM, inventory, Atlas Intercept, handheld scanning, APIs, integrations, routing, storytelling, learning, and partner workflows. Returns the related public APIs, partner access paths, production capabilities, current MCP tools, learning opportunities, and access requirements for each solution.
datasynch
get_datasynch_run_status
Support Atlas DataSynch operations by retrieving recent processing and workflow status for an authorized company, workspace, or manifest. Agents can use the result to explain integration progress, identify stalled activity, and understand the current state of EDI, EDIFACT, cXML, API, file, telemetry, inventory, location, and partner-data workflows.
failed
get_failed_runs
Help support, implementation, operations, and partner agents investigate failed Atlas DataSynch activity across APIs, files, EDI, EDIFACT, cXML, mappings, inventory, telemetry, locations, and downstream workflows. Returns authorized failure and exception context without changing workflow records.
manifest
get_manifest_summary
Retrieve authorized Atlasemoji manifest context so an agent can understand the places, routes, boundaries, layers, records, workflow purpose, workspace relationship, and operational context represented by the manifest.
point
check_point_in_geofence
Evaluate whether a vehicle, shipment, mobile device, scan, person-authorized location event, asset, aircraft, vessel, or other coordinate is inside a proposed radius boundary used in Atlasemoji geofencing and event-driven workflows.
suggest
suggest_field_mapping
Suggest an initial bridge between external partner, API, ERP, WMS, TMS, CRM, file, EDI-normalized, EDIFACT-normalized, cXML-derived, inventory, telemetry, item, and location fields and common Atlasemoji data targets. Intended to support integration design and human-reviewed mapping preparation.
summarize
summarize_workspace_activity
Summarize recent authorized activity across an Atlasemoji company, workspace, or manifest so agents can explain what has happened across DataSynch, locations, manifests, integrations, telemetry, exceptions, inventory, partner workflows, and operational records.

Endpoints

URLTransportStateLatencyChecked
https://atlasemoji.com/api/mcp streamable-http answering 211 ms 12 min ago

Atlasemoji — questions

Answers built from our own checks of this server.

What can Atlasemoji do?
It exposes 17 tools, read directly from the server on our last check. Among them: check_point_in_geofence, detect_file_schema, detect_location_columns, get_datasynch_run_status, get_failed_runs, get_manifest_summary and 11 more. The full list with descriptions is on this page — we take it from the server itself via tools/list, not from a README. How MCP servers expose tools in the first place →
What is Atlasemoji mostly used for?
Its tools cluster around validate, wanderloop and preview. That is what this server is built to work with — the grouping comes from the actual tool names, not from a category we assigned.
Is Atlasemoji working right now?
We send a real MCP handshake every 15 minutes. Over the last 24 hours 91 of 91 checks got a reply (100.0%), average response time 330 ms. The bar chart above shows every period we have measured.
How do I connect Atlasemoji?
Copy the ready config from this page — we generate it for Claude Code, Claude Desktop, Codex, Cursor and VS Code, each with the file path that client actually reads. It is a remote server, so there is nothing to install — the client connects to the address.
Does Atlasemoji need an API key?
No. Atlasemoji completed a full MCP handshake with us as an anonymous client and listed its tools without asking for anything. All 17 of them are readable on this page. This is what we observed, not what the docs claim.
How fast is Atlasemoji?
It answers our handshake in 330 ms on average, which is faster than 43% of all working MCP servers we measure. The comparison comes from our own checks across the whole registry, every 15 minutes.