Public Data Ukraine Mcp
Server Details
Public Data Ukraine Mcp connects AI agents to real public APIs via MCP. Tools include
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- varvararatta/botfactory-mcp
- GitHub Stars
- 0
Tool Definition Quality
Average 3.5/5 across 5 of 5 tools scored. Lowest: 2.7/5.
Each tool has a clearly distinct purpose: geocoding, exchange rates, weather, health check, and procurement search. No overlap exists.
Most tools follow a verb_noun snake_case pattern (geocode_ukraine, get_exchange_rates, get_weather_ukraine, search_prozorro_tenders). health_check is a minor deviation but still clear.
With 5 tools, the server is well-scoped for a focused public data API. Each tool addresses a distinct need without being overwhelming.
Covers geocoding, finance, weather, and procurement, but misses other common public data like demographics, transportation, or news. The health_check tool is not a data tool, reducing coverage.
Available Tools
5 toolsgeocode_ukraineBInspect
Geocode Ukrainian address to coordinates using OpenStreetMap Nominatim. Returns: {lat, lon, display_name, region, city}
| Name | Required | Description | Default |
|---|---|---|---|
| address | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. The description does not disclose behavioral traits such as reliance on external service (OpenStreetMap Nominatim), rate limits, error handling for invalid addresses, or data freshness. Only output format is mentioned.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is brief (two sentences) and front-loaded with purpose. No redundant information, but could be more efficient by integrating output format into first sentence.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations or output schema, the description covers basic input/output but lacks usage guidance, error scenarios, and constraints. It is adequate for a simple tool but incomplete for robust usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'address' has 0% schema description coverage. The description does not clarify required format, components, or restrictions beyond 'Ukrainian address'. The primary focus is on output, not input semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's verb (Geocode), resource (Ukrainian address), and output (coordinates). It distinguishes from sibling tools like get_exchange_rates or get_weather_ukraine by specifying geographic and functional context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use or not use this tool, nor any alternatives. The purpose implies geocoding of Ukrainian addresses, but prerequisites or constraints (e.g., address must be in Ukraine) are not stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_exchange_ratesAInspect
Get official NBU (National Bank of Ukraine) exchange rates. date format: YYYYMMDD or None for today. Returns: {rates, date, source}
| Name | Required | Description | Default |
|---|---|---|---|
| date | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the behavioral disclosure. It states the return structure {rates, date, source}, which is helpful. However, it does not explicitly mention that it is a read-only, idempotent operation or any potential side effects, leaving room for slight ambiguity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences: first states purpose, second provides parameter format and return structure. Every word earns its place; no superfluous content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (1 optional param, no output schema), the description completely covers what an agent needs: purpose, parameter format, and return format. No gaps remain.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema only defines the 'date' parameter as string|null with no description. The description adds significant meaning: 'date format: YYYYMMDD or None for today.' This fully compensates for the 0% schema description coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves official NBU exchange rates. The verb 'Get' and resource 'exchange rates' are specific. Siblings like geocode_ukraine, get_weather_ukraine, etc., are clearly distinct.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides the date format and default behavior (None for today). While it doesn't explicitly state when to use vs alternatives, the simplicity and distinct sibling names make the usage clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_weather_ukraineAInspect
Get current weather for Ukrainian city using Open-Meteo (free, no auth). Returns: {temperature_c, windspeed, weathercode, city}
| Name | Required | Description | Default |
|---|---|---|---|
| city | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses the data source (Open-Meteo), authentication requirement (none), and return fields. However, it does not mention rate limits, error handling, data freshness, or city name format.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences: one for purpose and source, one for return format. No redundant or vague phrasing. Every word adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple 1-parameter tool with no output schema, the description covers purpose, source, auth, and return fields. It would benefit from mentioning city format, but overall it is fairly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It adds that the city must be Ukrainian, providing some context beyond the schema's bare type string. It does not specify format (language, case), which could be ambiguous.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get current weather for Ukrainian city', which directly matches the tool name and identifies the specific resource (Ukrainian city). Sibling tools like geocode_ukraine, get_exchange_rates, health_check, search_prozorro_tenders are clearly distinct in purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use: for current weather in Ukrainian cities. It does not explicitly exclude cases or mention alternatives, but the narrow scope and sibling tool differentiation make usage clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
health_checkBInspect
Server health check.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits, but it only says 'health check' without detailing what the tool does (e.g., ping, status code, latency), side effects, or authorization needs.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no wasted words. It is front-loaded but could be slightly more structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and minimal context, the description is incomplete. It does not describe the return value or behavior, leaving an agent uncertain about what to expect from the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has no parameters and schema coverage is 100%, so the description need not add parameter details. Baseline 4 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Server health check.' clearly indicates the tool checks server health, and it is distinct from sibling tools like geocode_ukraine or get_exchange_rates. However, it could be more specific about what aspects of health are checked.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidelines are provided. The description does not explain when to use this tool versus alternatives, such as before other calls to verify server availability.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_prozorro_tendersCInspect
Search Ukrainian public procurement tenders on Prozorro. Returns: {tenders: [{title, value, status, date_modified}]}
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| keyword | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. Description only shows return format but no details on behavior like rate limits, pagination, or side effects. Minimal disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Short and front-loaded but lacks essential details. Could be more informative while still concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 2 parameters, no output schema, and no annotations, description omits important context like limit behavior, pagination, or result ordering. Incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage 0%; description does not explain 'keyword' or 'limit' beyond the schema. No added meaning for parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states verb 'Search', resource 'Ukrainian public procurement tenders on Prozorro'. Siblings are unrelated tools, so no confusion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool over alternatives or when not to use it. Lacks context for when to invoke.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Frequently Asked Questions
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Open the connector listing, choose Claim ownership, and sign in to Glama.
Complete one verification method:
GitHub identity — fastest for official registry listings. For a namespace such as
io.github.alice/server, link the matching GitHub user or an account that owns the GitHub organization, then choose Claim with GitHub.HTTP challenge — works when you can deploy a public file. Generate a token, publish the exact JSON Glama shows at
/.well-known/glama.jsonon the same origin as the connector, then choose Check HTTP challenge.DNS challenge — works when you control DNS but cannot change the server. Generate a token, create the exact TXT record Glama shows, wait for it to propagate, then choose Check DNS challenge.
After verification, Glama sends a confirmation email and gives you access to listing details, thumbnails, health checks, and analytics. Keep the HTTP file or DNS record in place: Glama periodically checks it and ownership remains verified while the token is discoverable.
The HTTP ownership file has this structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"claim": "glama_claim_..."
}Claim tokens are opaque, stable, and bound to the signed-in Glama account. They contain no email address or other personal information. If Glama can no longer discover a verified HTTP or DNS token, it starts a seven-day grace period before removing claim-based access. Restore the same token during that period to keep ownership verified. Never publish an email address, Glama session token, GitHub token, or connector credential as ownership proof.
If verification fails, confirm that you copied the current token exactly. The HTTP file must be public, return valid JSON with a successful HTTP response, and stay on the connector's origin. DNS changes may need more time to propagate. A claim cannot transfer to a different origin or hostname: if the connector target changes, Glama starts the grace period and the new target must be claimed separately after the previous claim is released.
For a connector linked to the official MCP Registry, registry updates continue to replace its name, description, and URL by default. After claiming, open Manage connector and enable Use Glama listing details as the source of truth if edits made on Glama should be preserved. Categories and thumbnails are always managed on Glama; registry linkage and technical connection settings continue to sync.
Control your server's listing on Glama, including description and metadata
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Feature your server to boost visibility and reach more users
To improve your MCP server's ranking:
Claim ownership of the server listing
Complete the server profile with an accurate description and thumbnail
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Keep tool definitions clear and complete to earn a high Tool Definition Quality Score (TDQS)
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For users:
Full audit trail – every tool call is logged with inputs and outputs for compliance and debugging
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For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
Tool-level analytics – see which tools are being used most, helping you prioritize development and documentation
Direct user feedback – users can report issues and suggest improvements through the listing, giving you a channel you would not have otherwise
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The server is experiencing an outage
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Credentials required to access the server are missing or invalid
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