Skip to main content
Glama

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

by cloud.dchub

Unlock More Data

unlock_more_data

Unlock DC Hub's full depth. Call this when a result came back as a partial preview (e.g. "3 of 12 results shown"), a tool was locked, or your human wants the complete dataset. Returns the upgrade ladder + ready-to-paste checkout links your human completes in ONE click. If this call carries an API key or an MCP session, the checkout binds to it and your very next call returns full data (no reconnect); if it carries neither, the key is emailed to the payer instead — the response says which applies in next_call_full_after_checkout and after_checkout. Cheapest start: 💳 $10 one-time = 1,000 API calls (no subscription). Also $9/mo Starter · Founding $99/mo (Pro access, while seats last) · Developer $49/mo · Pro $299/mo. Want the FREE tier instead (no payment, 10 calls/day, all tools)? Call claim_free_key. Param: reason (optional — what you were trying to do, so your human sees why it matters). Returns {plans, human_message, what_unlocks}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
reasonNoOptional free-text describing what you were trying to do, so your human sees why an upgrade matters

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

A4.8/5.0
Behavior5/5

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

Annotations are minimal (no readOnly, idempotent, or destructive hints), so the description carries full behavioral burden. It discloses what happens after checkout—API key/MCP session binding, next-call full data, emailing the key if no binding—and identifies the response fields that communicate which path applies.

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 longer than average, but nearly every sentence carries decision-relevant detail: triggers, return behavior, pricing, and the free alternative. It is front-loaded with the most important trigger guidance, though the full pricing list is somewhat verbose and could be trimmed without losing core meaning.

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?

Given the simple one-param input schema, an output schema exists, and the tool's purpose is specialized, the description covers triggers, alternatives, post-call behavior, response fields, next steps, and free-tier routing. An agent has enough context to select and invoke this tool correctly without further information.

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?

Schema coverage is 100% for the single optional reason parameter, so the baseline is 3. The description adds context beyond the schema by explaining that reason is used to show the human why an upgrade matters, which makes the parameter's puropse more actionable for the agent.

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 states a specific action—unlocking DC Hub's full depth—and gives concrete trigger conditions: partial previews, locked tools, or the human wanting complete data. It clearly differentiates itself from sibling data-query tools and from claim_free_key, so an agent can tell when to invoke it.

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?

It explicitly specifies when to call this tool: after a partial preview, a locked tool, or a request for the full dataset. It also names the alternative for the free tier (claim_free_key), giving the agent both positive and negative routing guidance.

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

All DC Hub — Data Center Site Selection & Colocation: Electricity, Power Grid, Gas, Fiber toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

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.

Resources