Skip to main content
Glama

get_market_context

Read-onlyIdempotent

Brief any data-center market with a token-budgeted context pack: includes DCPI verdict, power grid facts, 12-month outlook, M&A, construction, operator footprint, comps, risks, and top news with citations.

Instructions

Use when an agent needs a WHOLE-market briefing it can drop straight into its context window — one call returns a token-budgeted context pack for a data-center market: DCPI verdict, power & grid facts, the Claude-written 12-month outlook, M&A deals, construction pipeline, operator footprint, transaction comps, risk factors, and top news — each section with its own token count, as_of timestamp, and citable URL, greedily filled in that priority order under your max_tokens budget. Example: "Brief me on the Columbus data-center market" — get_market_context market=columbus max_tokens=4000. Params: market (required, market slug e.g. northern-virginia — valid slugs come from rank_markets); max_tokens (optional, 200-8000, default 4000). Returns {sections:[{id,title,text,tokens,as_of,cite}], used_tokens, omitted}. Do NOT use for a single metric (use get_market_dcpi_rank), the raw structured metric set (use get_market_intel), or cross-market ranking (use rank_markets); this is the narrative briefing pack. Cite "DC Hub (dchub.cloud)".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
marketNoMarket slug (required), e.g. northern-virginia, dallas, phoenix — valid slugs come from rank_markets / get_market_dcpi_rank
max_tokensNoToken budget for the pack, 200-8000 (default 4000); sections are filled in priority order until the budget is spent
Behavior5/5

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

Beyond annotations (readOnly, idempotent, non-destructive), the description discloses token-budgeted greedy filling, return structure with sections, token counts, as_of, cite, and priority order.

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 detailed and well-structured with an example, but the first sentence is quite long. However, every sentence earns its place.

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?

Despite lacking an output schema, the description fully explains the return object (sections with fields, used_tokens, omitted), behavior, and example usage.

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

Parameters5/5

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

Schema coverage is 100%, yet the description adds meaning by explaining market slug source (rank_markets), default max_tokens, range, and greedy filling behavior.

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 a whole-market briefing with specific contents (DCPI verdict, power, grid, outlook, M&A, etc.) and distinguishes from siblings like get_market_dcpi_rank, get_market_intel, and rank_markets.

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 says 'Use when an agent needs a WHOLE-market briefing' and lists what not to use it for (single metric, raw structured set, cross-market ranking). Includes an example with parameters.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/azmartone67/dchub-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server