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Glama
jnguyen-coder

govtenders-mcp

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault

No arguments

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Features and capabilities supported by this server

Protocol revision2025-11-25

CapabilityDetails
tools
{
  "listChanged": true
}
resources
{
  "listChanged": true
}

Tools

Functions exposed to the LLM to take actions

NameDescription
get_tender_statsA

Get current government tender statistics including active tender count, covered industries, and available countries (Canada + United States). Use this to check what data is available before searching.

search_tendersA

Search government tenders by industry, region, country, or value range. Returns matching tenders from CanadaBuys (Canada) and SAM.gov (United States). Covers 11,000+ active contract opportunities across 45 industries. Use industry keywords like: construction, IT, consulting, healthcare, defense, transportation, environmental, engineering, security, facilities.

get_latest_tendersA

Get the latest government tenders published in the last 24-48 hours. Returns newest tenders sorted by publication date from both CanadaBuys and SAM.gov.

match_tendersA

AI-powered semantic matching. Describe your business, capabilities, or expertise and get ranked tender matches scored by relevance. Uses Claude Haiku for intelligent matching across 11,000+ tenders.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription
service-info

TDQS

A4.1/5.0

Scored across 4 tools

Disambiguation5/5

Each tool has a clearly distinct purpose: stats overview, structured search, recent tenders, and semantic matching. While search_tenders and match_tenders both return tenders, their input methods and intended use cases are well-differentiated by the descriptions.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern with snake_case: get, search, get, match. The names are predictable and clearly indicate the action being performed.

Tool Count5/5

Four tools is an appropriate and well-scoped set for a government tender discovery server. Each tool covers a distinct need without unnecessary overlap or bloat.

Completeness4/5

The tool surface covers the main discovery workflows: checking stats, searching with filters, getting latest updates, and semantic matching. A minor gap is the lack of a dedicated tool to fetch full details of a specific tender by ID, but the provided tools likely return sufficient information for most workflows.

Maintenance

ActivityInactive
ResponsivenessNo issues