com.atlasemoji/mcp · v0.1.0 · agents-and-memory
Atlasemoji is healthy: it completed an MCP handshake in 736 ms and exposes 19 tools.
AI-ready GIS, geofencing, DataSynch, CRM, inventory, routing, APIs, telemetry and workflows.
Endpoint: https://atlasemoji.com/api/mcp (streamable-http)
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| Users (last 30 days) | 0 |
| Handshake | Healthy |
| Auth needed | None |
| Tool count | 19 |
| Latency | 736 ms |
| Last checked (UTC) | 2026-10-15T19:15:19.498Z |
| Checked (UTC) | Status | Latency | Error |
|---|---|---|---|
| 2026-10-15T19:15:19.498Z | Healthy | 736 | |
| 2026-10-14T18:10:49.699Z | Healthy | 2673 |
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, learni |
get_atlas_profile | Return the Atlasemoji profile represented by the current authenticated MCP credentials so ChatGPT can identify the connected Atlas account. This operation is read-only and never accepts a user or account identifier from the model. |
verify_atlas_agent | Complete proof of life for an already configured Atlas Agent MCP connection. The authenticated MCP principal must be authorized for the requested company and for this tool. Atlas verifies that the connection belongs to the requested Agent and records the current Manifest revision before returning a |
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 |
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. |
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. |
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. |
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. |
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_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 |
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. |
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. |
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. |
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_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. |
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, provi |
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 |