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Glama

DC Hub — Data Center Site Selection & Colocation: Electricity, Power Grid, Gas, Fiber

Get Facility Details

get_facility
Read-onlyIdempotent

Full metadata for one facility — name, operator, address, lat/lon, power capacity (MW total/used), cooling type, fiber providers (count + carrier list), commissioning year, status, the DCPI verdict for its market, and peer facilities nearby. Answers "who operates this data center and how big is it", "how many fiber carriers are in that building". Try: get_facility id=equinix-dc1-ashburn — or get_facility slug=digital-realty-iad8. Returns ONE facility in full; do NOT use to search or list many facilities (use search_facilities).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNoAlias for facility_id — a facility id/slug from a prior search result
nameNoFacility name as a fallback lookup when no id/slug is known, e.g. "QTS Ashburn"
slugNoFacility slug from a prior search result, e.g. digital-realty-iad8
facility_idNoFacility id from a prior search_facilities/search result (numeric or string), e.g. equinix-dc1-ashburn
include_powerNoInclude power capacity detail (total/used MW) in the response (default true)
include_nearbyNoInclude peer facilities near this one in the response (default true)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
quotaNoCaller quota state (remaining calls, tier) when available.
_entityNoPayload class discriminator (e.g. facility|market|iso_grid|queue_results|deal|report|response) — branch on this before parsing the rest.
citationNoMachine-readable citation: how to attribute DC Hub (dchub.cloud) for this payload. Normally an OBJECT {source, url, license, cite_as, retrieved_at}; a bare string is accepted and carries the attribution line itself.
provenanceNoCollection-level provenance block: {source, method, as_of, verification_counts, cite_url_template, license, cite_as}. Quote the verification level when citing.
_front_doorNoIn-band front-door hint (first workflow-entry tool of a session): call plan_query(intent) first for the ordered multi-step plan.
_return_loopNoSuggested next-session delta call (get_changes since=24h) so you pull only what changed.
site_evaluation_handoffNoPre-built follow-up calls (analyze_site / get_water_risk args) when the payload carries coordinates — an array of {tool, parameters, why} entries.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, so the safety profile is covered. The description adds context by specifying that it returns exactly one facility in full and enumerates the data categories included, plus the boundary that it should not be used as a search/list tool. No contradiction with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with core scope and data list, followed by examples and an explicit exclusion. It is detailed but efficient; minor redundancy exists between 'Full metadata for one facility' and 'Returns ONE facility in full'.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With 100% schema coverage, annotations, an output schema, and example invocations provided, the agent has sufficient information to invoke the tool correctly. Domain specifics like DCPI verdict are not required for invocation and are adequately mentioned as part of the return data.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, with all six parameters documented in the input schema. The description's example id/slug values add concrete usage hints but do not materially extend the schema-provided semantics. Baseline 3 is appropriate since the schema carries the parameter documentation burden.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description begins with 'Full metadata for one facility' and enumerates specific fields (name, operator, address, lat/lon, power capacity, cooling type, fiber providers, commissioning year, status, DCPI verdict, peer facilities), giving a clear verb+resource. It also distinguishes itself from search_facilities by explicitly saying 'Returns ONE facility in full; do NOT use to search or list many facilities'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states the single-facility lookup use case and provides concrete examples: 'Try: get_facility id=equinix-dc1-ashburn — or get_facility slug=digital-realty-iad8'. It also names the alternative tool for list/search operations: 'use search_facilities'.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A4.1/5.0
Disambiguation2/5

Multiple tools occupy nearly identical semantic space: search/search_facilities/search_intelligence/semantic_search all retrieve data, and analyze_site/compare_sites/score_facility/get_composite_site_score/rank_sites all score or rank locations. Despite extensive disambiguation in the descriptions, the boundaries are subtle enough that an agent will likely misroute queries. Account and meta tools (claim_free_key, bind_email, unlock_more_data, subscribe_digest, recover_my_key, execute_plan, plan_query, discover_tools) add further selection noise.

Naming Consistency4/5

The vast majority of tools follow a clear snake_case verb_noun convention (get_*, search_*, list_*, set_*, save_*, compare_*, analyze_*, rank_*, plan_*). A few noun-phrase names break the pattern (deal_autopsy, hyperscaler_deals, grid_transition_radar, site_selection_canvas, standing_intent, ai_capacity_index), but these are still readable and discoverable.

Tool Count1/5

83 tools is an extreme count for any server, far beyond the 25+ threshold that already signals bloat. The domain is broad, but the catalog is inflated by overlapping variants, multiple meta-tools (execute_plan, plan_query, discover_tools, get_agent_registry, get_backup_status, summarize_for_citation), and account/upgrade plumbing (claim_free_key, bind_email, recover_my_key, unlock_more_data, subscribe_digest). This imposes heavy context and selection costs on agents.

Completeness5/5

The data-center siting domain is covered exhaustively: single-site scoring, market ranking, grid/gas/fiber/water/climate/disaster/tax/permitting intelligence, interconnection queues, construction pipeline, deals/news, saved-site monitoring, alerts, research dossiers, and citation support. Every workflow has a continuation path, so agents will not hit dead ends.