irish-competition-mcp

Server Quality Checklist

Profile completionA complete profile improves this server's visibility in search results.

Latest release: v0.1.0
Disambiguation5/5
Each tool has a distinct purpose: search vs. get for decisions and mergers, plus list_sectors and about. There is no overlap or ambiguity between tools.
Naming Consistency5/5
All tools share the 'ie_comp_' prefix and follow a clear verb_noun pattern (search_decisions, get_decision, search_mergers, get_merger, list_sectors). The 'about' tool is a conventional exception for metadata, but the pattern remains highly consistent.
Tool Count5/5
Six tools is well-scoped for a read-only competition law database. Each tool serves a necessary function without redundancy or bloat.
Completeness5/5
The tool set covers the full lifecycle for this domain: search and retrieve both decisions and mergers, browse sectors, and access server metadata. As a read-only API, no create/update/delete operations are expected, so there are no obvious gaps.
Average 4/5 across 6 of 6 tools scored.
See the Tool Scores section below for per-tool breakdowns.
This repository is archived. Archived repositories automatically receive an F maintenance tier.
This repository is licensed under Apache 2.0.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description discloses no behavioral traits such as read-only nature, response format, or error conditions. For a tool with no annotation coverage, the description carries the full burden, and it is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, front-loaded with the action, and includes concrete examples. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with one parameter, but lacks an output schema and annotations. The description does not explain what the response contains or behavior when the case number is not found. It is minimally acceptable but leaves gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already describes case_number with the same examples. The description adds no additional meaning beyond the schema, so it meets the baseline but does not exceed it.
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 a specific verb ('Get') and resource ('specific CCPC decision') and distinguishes from sibling search tools by specifying lookup by case number. It is unambiguous and concise.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when you know the case number, but it does not explicitly say to use a search tool when the case number is unknown. Sibling 'ie_comp_search_decisions' exists, but no alternative or exclusion is mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It only states that it retrieves a decision, without detailing any behavioral traits such as error handling, return format, or permissions. The 'Get' verb implies a read operation, but no additional context is provided.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence that front-loads the verb 'Get' and includes necessary examples. It is appropriately concise and readable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple, with one parameter and no output schema. The description clearly states the purpose and parameter, making it sufficient for an agent to understand when to use it. However, it omits any detail about the response structure or potential errors, which is a minor gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides full coverage with the same example strings ('B1-35/21', 'B8-101/18'). The description's examples duplicate the schema, so no new parameter meaning is added.
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 uses the specific verb 'Get' and identifies the resource as 'merger control decision' with the criteria 'by case number'. This clearly distinguishes it from sibling tools like search_mergers and get_decision, which have different purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies that this tool should be used when a specific case number is already known, but it does not explicitly state when to use alternatives or when not to use it. There is no mention of using search tools first or differentiating from get_decision for non-merger decisions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden of disclosing behavior. It does state that the tool 'returns merger cases' with specific fields, giving some behavioral insight. However, it omits details such as whether the search is read-only, how results are ordered, or any pagination or authorization requirements. This is acceptable but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that states the tool's purpose and key output fields. It contains no filler or redundancy, making it highly concise and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a search tool with four parameters and no output schema, the description provides a clear summary of return fields while the schema covers parameter details. It does not elaborate on interaction between filters (e.g., whether sector and outcome are combined), but the core usage is clear. This is reasonably complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, meaning each parameter (query, limit, sector, outcome) is documented in the schema. The description adds no additional parameter-level detail beyond what the schema already provides. Therefore, the description carries no extra semantic burden, netting a baseline '3'.
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's function: 'Search CCPC merger control decisions (Fusionskontrolle).' It uses a specific verb ('search') and resource ('merger control decisions'), and distinguishes from sibling tools like ie_comp_search_decisions by focusing specifically on merger cases. The return fields ('acquiring party, target, sector, and outcome') further clarify scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is for merger-specific searches, contrasting with more general decision search tools. It provides clear context (CCPC merger control) but does not explicitly state when not to use it or name alternatives. Since the sibling list suggests ie_comp_search_decisions for general decisions, the guidance is adequate but not fully explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden of indicating behavior. The words 'search' and 'returns' clearly imply a non-destructive read operation, and the return fields are disclosed. It does not mention rate limits or authentication, but for a search tool, the safety profile is adequately conveyed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is exactly two sentences, with the first stating the primary purpose and scope, and the second listing the return fields. It is front-loaded, precise, and contains no redundant words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description omits that the tool supports additional filters (type, sector, outcome, limit) and introduces a potential ambiguity: the schema includes 'merger' as a type, while the description lists only enforcement categories, suggesting mergers are out of scope. This mismatch should be explicitly clarified to avoid incorrect usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema provides 100% descriptive coverage for all five parameters, so the description does not need to re-explain them. The tool description reinforces the type enum by listing examples in the text, but it adds no unique parameter-level detail beyond the schema.
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 a specific action (full-text search) on a well-defined resource (CCPC enforcement decisions), lists the covered categories (abuse of dominance, cartel, sector inquiries), and distinguishes from sibling merger search tools by explicitly limiting scope to enforcement decisions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for the tool's domain (enforcement decisions) and indirectly differentiates it from the sibling merger search tool, but it does not explicitly state when not to use it or name alternative tools. The scope is unambiguous enough for an agent to decide correctly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states the tool lists all sectors with activity and includes counts, giving useful behavioral detail. However, it does not disclose ordering, pagination, or any potential exclusions beyond 'with CCPC enforcement activity,' so it stops short of fully transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
One sentence that is front-loaded and contains no waste. Every phrase adds 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?
The description explains purpose and return data (counts per sector) despite lacking an output schema. For a simple zero-parameter list tool, this is adequately complete.
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?
The tool has zero parameters, so the baseline is 4. There is nothing to add beyond the schema.
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 identifies a specific verb ('List'), a clear resource ('sectors'), and a scope ('with CCPC enforcement activity'). It also specifies the output includes decision and merger counts, distinguishing it from sibling search/get tools that operate on individual decisions or mergers.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the appropriate use case (sector-level overview of enforcement activity) but does not explicitly mention alternatives or when not to use. It provides clear context without exclusions, earning a 4 per the rubric.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of disclosure. It explicitly states the output includes version, data source, coverage, and tool list, making it clear this is a read-only metadata operation. No hidden side effects or destructive behavior are implied, and the description is honest about its scope.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, front-loaded with the verb and resource, and lists the four key metadata items. Every word earns its place; there is no redundancy or filler.
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?
For a simple about tool with no parameters, the description fully covers the purpose and return value. The lack of an output schema is mitigated by the explicit enumeration of returned fields. Complexity is low, and no additional context is needed for an agent to invoke this tool correctly.
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?
The tool has zero parameters, and the baseline for 0 params is 4. The description adds value beyond the empty schema by specifying what the tool returns, which is the entire semantic content. No parameter details are needed, and the description fully compensates for the void in the schema.
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 uses a specific verb ('Return') and identifies a clear resource ('metadata about this MCP server') with enumerated contents (version, data source, coverage, tool list). This clearly distinguishes it from sibling tools like ie_comp_search_decisions and ie_comp_get_decision, which are domain-specific data access tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly implies when to use this tool: when you need server-level metadata or a tool list. While it doesn't explicitly state exclusions or alternatives, the sibling tools are all about decisions/mergers/sectors, so the context is unambiguous. A dedicated 'about' tool is self-explanatory.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

GitHub Badge

Glama performs regular codebase and documentation scans to:

Confirm that the MCP server is working as expected.
Confirm that there are no obvious security issues.
Evaluate tool definition quality.

Our badge communicates server capabilities, safety, and installation instructions.

Card Badge

Copy to your README.md:

[![irish-competition-mcp MCP server](https://glama.ai/mcp/servers/Ansvar-Systems/irish-competition-mcp/badges/card.svg)](https://glama.ai/mcp/servers/Ansvar-Systems/irish-competition-mcp)

Score Badge

Copy to your README.md:

[![irish-competition-mcp MCP server](https://glama.ai/mcp/servers/Ansvar-Systems/irish-competition-mcp/badges/score.svg)](https://glama.ai/mcp/servers/Ansvar-Systems/irish-competition-mcp)

Latest Blog Posts

Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)
By Om-Shree-0709 on July 25, 2026.
mcp
Agent Identity
OAuth 2.1
Your AI Chatbot Just Exposed Your CEO's Salary to an Intern
By Om-Shree-0709 on July 2, 2026.
Agent Identity
MCP Security
OAuth Delegation
Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)
By Om-Shree-0709 on June 30, 2026.
Agentic Ai
Prompt Injection
WebAssembly

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/Ansvar-Systems/irish-competition-mcp'

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