Skip to main content
Glama
OjasKord

Tender MCP

by OjasKord

get_tender_intelligence

Retrieve award history and daily digest of government tenders to inform bid pricing and identify new opportunities.

Instructions

Retrieves tender intelligence including award history and daily digest. Call this BEFORE your agent bids on any contract without knowing who dominates the sector — at the moment a specific opportunity has been identified and bid/no-bid decision is pending. Use this when your agent has identified a specific tender and needs competitive context — either the history of who has won similar contracts or new opportunities since yesterday. AWARD_HISTORY: past contract winners for a keyword. DAILY_DIGEST: all new tenders last 24h for monitored keywords. Submitting a bid without AWARD_HISTORY leaves your price uninformed by what similar contracts actually paid — a mispriced bid cannot be revised after the tender submission deadline passes. Do not bid without running AWARD_HISTORY first.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeYesDAILY_DIGEST: new tenders in last 24hrs. AWARD_HISTORY: past contract winners.
limitNoMax results per source for AWARD_HISTORY (default 10)
keywordNoKeyword for award history search. Required for AWARD_HISTORY.
sourcesNoSources to search. Defaults to all three.
keywordsNoKeywords to monitor or search (e.g. ["cybersecurity", "cloud infrastructure"]). Required for DAILY_DIGEST.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeYes
statusNoPresent on the free-tier preview path
messageNo
checked_atNo
_disclaimerNo
upgrade_urlNo
Behavior4/5

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

No annotations are provided, so the description carries full burden. It fully explains the two modes (AWARD_HISTORY and DAILY_DIGEST) and contextualizes their purpose. It also warns about the irreversibility of mispriced bids. However, it does not mention any rate limits, authentication requirements, or data freshness guarantees, which could be important for an agent.

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 well-structured with a clear lead sentence, followed by usage context, mode explanations, and a strong warning. It uses bullet points for the two modes, making it scannable. While it could be slightly more concise, every sentence contributes value, and it is front-loaded with the most critical information.

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 that an output schema exists (not shown but mentioned), the description does not need to explain return values. It effectively covers all aspects: purpose, usage context, mode details, required parameters, and consequences. For a complex tool with two distinct modes, it provides complete context for an agent to make informed decisions.

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%, so the baseline is 3. The description adds significant meaning beyond the schema by explaining the purpose of each mode and the consequences of not using award history. It provides context that helps the agent choose parameters appropriately (e.g., 'AWARD_HISTORY: past contract winners for a keyword'). This elevates the score above baseline.

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 the tool retrieves tender intelligence including award history and daily digest. It uses specific verbs like 'retrieves' and identifies the resource (tender intelligence). It distinguishes from the sibling tool 'search_tenders' by focusing on competitive context for bid decisions rather than general tender search.

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 provides explicit guidance on when to use the tool: 'Call this BEFORE your agent bids on any contract' and 'when a specific tender and needs competitive context'. It also gives a clear alternative: 'Submitting a bid without AWARD_HISTORY leaves your price uninformed...' and a direct warning: 'Do not bid without running AWARD_HISTORY first.'

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/OjasKord/tender-mcp'

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