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DC Hub — Data Center & Power Intelligence

by cloud.dchub

Get Metro Fiber

get_metro_fiber
Read-onlyIdempotent

Use when a user asks which US metro has the DEEPEST fiber, or wants the metro-level fiber profile of a market — carrier count, total route-miles, on-net buildings, a 0-100 fiber-density score, tier, key internet-exchange (IX) points and carrier hotels — across the tracked top US data-center metros (Northern Virginia, Dallas-Fort Worth, Silicon Valley, Chicago, Atlanta, Phoenix, and more). Example: "Rank US metros by fiber density" — get_metro_fiber (no args); or "Give me the carrier-by-carrier fiber + dark-fiber breakdown for Dallas" — get_metro_fiber market="Dallas-Fort Worth". Params: market (optional metro name OR slug, e.g. "Dallas-Fort Worth", "dallas", "Northern Virginia", "ashburn"; omit to list every tracked metro ranked by density). Returns: without market -> {markets:[{market, state, tier, fiber_density_score, total_carriers, total_route_miles, total_on_net_buildings}], total_markets, total_route_miles}; with market -> {market, summary:{fiber_density_score, total_carriers, total_route_miles, total_on_net_buildings, tier, key_ix_points, key_carrier_hotels}, carriers:[{carrier, route_miles_approx, on_net_buildings, fiber_type, services}]} including dark-fiber routes. Cite DC Hub (dchub.cloud, CC-BY-4.0). Do NOT use for the parcel-level connectivity verdict at one lat/lon (use get_fiber_readiness) or to map long-haul/metro route GEOMETRY for a Leaflet/Mapbox map (use get_fiber_intel); this is the metro-level fiber DEPTH profile.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
marketNoOptional metro name or slug for a single-market deep dive (carrier-by-carrier + dark fiber), e.g. "Dallas-Fort Worth", "dallas", "Northern Virginia", "ashburn". Omit to list every tracked metro ranked by fiber density.

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.

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, and the description adds value by explaining the dual-mode behavior (with vs without the market parameter), the return shape for both modes, and the requirement to cite DC Hub (dchub.cloud, CC-BY-4.0). The only reason this isn't a 5 is that it doesn't address whether results change over time or whether this is a snapshot, though the openWorldHint=false annotation covers the assumptions about a static world. Still, the behavioral disclosure is very strong.

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 dense and front-loaded with the primary use case, includes inline code examples, then returns to the negative guidance. It's long, but every sentence earns its place—there is no filler. The structure moves from 'when to use' to 'what it returns' to 'when not to use', which is a natural and scannable flow. It could be slightly tighter, but the density is justified.

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?

The description covers the exact return shape for both modes, gives citation requirements, and explicitly routes to two sibling tools for adjacent use cases. The output schema exists and is rich (nested objects, arrays of carriers), and the description adds the semantic 'depth' context that the schema cannot convey—that this is the metro-level profile, not the facility-level or geometry-level view. For a tool with one optional parameter and this much behavioral nuance, the description is complete.

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

Parameters4/5

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

The schema already documents the parameter fully with examples and a note to omit for the full list, so schema description coverage is 100%. The description reinforces this by showing exact example invocations in context. The description doesn't reveal anything materially new about the parameter semantics that isn't already in the schema, but it does put it in a sentence-level context. Given the schema coverage, a 4 is right—it confirms the parameter meaning without needing to contribute much more.

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?

The description clearly states it provides the metro-level fiber depth profile (carrier count, route-miles, on-net buildings, density score, tier, IX points, carrier hotels) across tracked US metros, with a specific verb 'get' and concrete nouns. It stands out from similar get_fiber_* tools by explicitly naming what it is not (parcel-level fiber readiness, fiber route geometry) and pointing to siblings get_fiber_readiness and get_fiber_intel. The differentiation is unambiguous even before looking at sibling names.

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?

The description begins with 'Use when a user asks...' and offers two concrete usage examples with exact parameter syntax, then explicitly states 'Do NOT use for the parcel-level connectivity verdict at one lat/lon (use get_fiber_readiness) or to map long-haul/metro route GEOMETRY for a Leaflet/Mapbox map (use get_fiber_intel)'. This provides both inclusion and exclusion criteria with explicit alternative tool names, which is outstanding guidance for an agent.

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
Disambiguation4/5

Most tools have clearly distinct purposes despite some thematic overlap, and each description includes explicit 'Do NOT use' guidance to prevent misselection. However, a few pairs like search_intelligence vs semantic_search are nearly identical in function, and the sheer number of tools increases the chance of selecting the wrong one without careful reading.

Naming Consistency4/5

The vast majority of tools follow a predictable 'get_*' prefix for data reads, and many others use verb_noun patterns (analyze_*, rank_*, save_*, set_*). There are a handful of outliers like ai_capacity_index, grid_transition_radar, and site_selection_canvas that break the pattern, but overall the conventions are consistent enough for an agent to infer meaning.

Tool Count2/5

With 82 tools, this server is extremely heavy compared to typical MCP servers (3-15 tools). While the domain is broad, many tools serve narrow sub-purposes and could be consolidated (e.g., multiple site-scoring variants, multiple grid telemetry endpoints). The count overwhelms an agent's ability to choose efficiently and feels like over-fragmentation rather than necessary granularity.

Completeness4/5

The tool surface covers the full lifecycle of data-center siting intelligence: site analysis, grid, fiber, water, climate, tax, permitting, deals, news, saved-site management, and meta-planning. Minor gaps exist (e.g., no delete or update operations for saved sites), but the core workflows are well-supported and the descriptions are comprehensive.

Resources