MEOK DORA Tlpt Planner MCP

by CSOAI-ORG

Overview Schema Related Servers Score Discussions

Python

Local

Server Quality Checklist

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

Latest release: v1.0.3
Disambiguation5/5
Each tool targets a distinct purpose: listing phases, pricing, remediation milestones, scope document generation, signed attestation, and threat intel brief. No overlap in functionality, making selection unambiguous.
Naming Consistency3/5
Names use snake_case but mix verb_noun (list_phases, signed_tlpt_attestation) with plain nouns (pricing, remediation_milestones, scope_tlpt, threat_intel_brief). While readable, the pattern is inconsistent.
Tool Count5/5
With 6 tools, the server covers the key planning activities for DORA TLPT without being bloated or sparse. Each tool contributes meaningfully to the planner's purpose.
Completeness4/5
The set covers phases, pricing, remediation, scope, attestation, and threat intel scaffolding. A minor gap is the lack of a tool to input findings automatically, but the remediation_milestones tool accepts that data, so the core workflow is intact.
Average 3.9/5 across 6 of 6 tools scored. Lowest: 2.9/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- Last stable release on May 7, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
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.
This repository includes a glama.json configuration file.
This server has been verified by its author.
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 does not disclose any behavioral traits such as side effects, permissions, or rate limits. The agent has no insight into whether the tool is read-only or requires special access.
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 a single sentence with no redundancy, making it concise. However, it is so brief that it sacrifices necessary detail, which prevents a higher score.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With zero parameters and an output schema present, the description should explain what pricing information is returned (e.g., costs, tiers, or conditions). It fails to do so, leaving the agent without sufficient context to trust the tool's relevance.
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 tool has zero parameters, so baseline is 4. However, the description ('Pricing...') does not add value beyond the empty schema—it merely restates the tool name. It could describe the output structure or content, which is absent.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Pricing for MEOK DORA TLPT Planner,' indicating this tool provides pricing information. It distinguishes from sibling tools (e.g., list_phases, scope_tlpt) by focusing on pricing. However, it lacks a specific verb (e.g., 'get' or 'retrieve'), which would improve precision.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. There is no mention of context, prerequisites, or exclusions, leaving the agent to guess its appropriate role.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It indicates the action produces a signed attestation but does not disclose side effects, authorization requirements, or whether the action is idempotent. This is insufficient for safe invocation.
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 concise: a one-line purpose followed by a bullet-like list of arguments. It front-loads the purpose and uses no filler, but could be more structured (e.g., markdown formatting).
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 covers all input parameters and mentions the return value. However, it lacks constraints (e.g., signing_role values beyond the default) and does not explain the output schema in detail. The output schema exists but is not leveraged.
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?
With 0% schema description coverage, the description adds significant meaning: it explains the expected structure of findings_summary (dict with specific keys), lists enum values for test_phase, and notes the default for signing_role. This goes beyond the raw 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 the tool produces an HMAC-signed TLPT attestation via a specific API, and lists all arguments. It is distinct from sibling tools like list_phases or pricing, 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 usage when a signed attestation is needed, but does not explicitly state when to use this tool versus alternatives or provide any exclusion criteria.
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 present, so the description must disclose behavioral traits. It explains the output (a milestone plan with closure timelines) but does not mention side effects, authentication needs, or read-only nature. It is adequate but not 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a clear purpose line followed by Args and Returns sections. It is efficient and front-loaded, though could be slightly more concise.
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?
Given the tool's simplicity (2 parameters, output schema exists), the description covers inputs and output sufficiently. It provides a complete picture for usage without needing additional context.
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?
Despite 0% schema description coverage, the description adds significant meaning by explaining 'findings_count' as total findings and 'severity_distribution' as a dict with keys like critical, high, etc. This compensates for the schema gap.
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: 'Generate a 90/180/365-day remediation milestone plan based on TLPT findings.' It uses a specific verb ('Generate') and specifies the resource and context, distinguishing it from siblings like list_phases or pricing.
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 for generating plans from TLPT findings but does not explicitly state when to use this tool over alternatives, nor does it provide exclusionary guidance. Adequate but lacks comparative context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose any behavioral traits such as side effects, permissions, rate limits, or whether it is read-only. It only explains the scaffold nature but lacks essential behavioral context for a tool with no annotations.
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 concise with four sentences plus a parameter list. It front-loads the purpose and scaffold note, and every sentence is valuable. No redundant information.
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?
Given an output schema exists (but not shown), the description mentions the template aligns with standards. It explains all parameters adequately. However, it lacks details on error handling or behavior for invalid inputs, but overall is fairly complete for a template generator.
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?
The input schema has 0% description coverage, so the description fully compensates by explaining each parameter: entity_name is legal name, entity_sector lists allowed values, geographic_footprint expects country codes, and critical_functions are for threat modeling. This adds significant meaning beyond the schema titles.
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 generates a TTI brief template per ECB TIBER-EU v2.0, specifies it's a scaffold, and distinguishes it from siblings which are unrelated (e.g., list_phases, pricing). The verb 'Generate' and resource 'TTI brief template' are specific and unambiguous.
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 explicitly states that the template is a scaffold and that real TTI must be authored by an accredited provider, guiding users to use it for briefing providers. It does not explicitly mention when not to use or alternative tools, but the context is clear enough for a template generator.
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, the description carries the full burden. It correctly indicates a read-only listing operation with no side effects. No further behavioral details (e.g., auth) are needed given the tool's simplicity.
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 of 8 words, front-loaded with action ('List'), no wasted words. Perfect conciseness and clarity.
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?
Complete for a simple list tool with 0 parameters and an output schema. The description covers what is listed (3 phases, deliverables) and no additional context is necessary.
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?
No parameters exist, so baseline is 4. The description does not add parameter-specific information, but none is required.
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 lists 'the 3 TIBER-EU TLPT phases with deliverables,' using a specific verb and resource. It distinguishes from siblings like pricing or scope_tlpt, which cover different TIBER-EU aspects.
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?
No explicit guidance on when to use or avoid this tool vs alternatives. However, the set of siblings are distinct, so usage is implied for listing phases, but lack of explicit context lowers the score.
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 full burden. It discloses that the tool returns a structured scope document and outlines its contents (phase plan, deliverables, RACI, budget breakdown). This provides clear behavioral expectations, though it could explicitly confirm no 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with Args and Returns sections, and each sentence adds value. It is moderately concise, though the parameter explanations could be slightly more compact without losing clarity.
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 the tool's complexity (6 parameters, 2 required, has output schema), the description covers all parameters and the return value comprehensively. It provides sufficient context for an agent to invoke the tool correctly without ambiguity.
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 description coverage is 0%, but the description compensates by explaining each parameter in detail (e.g., allowed values for entity_type, default for sector, purpose of critical_functions, format for last_tlpt_date). This adds significant meaning beyond the schema's property names and types.
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?
Description clearly states 'Generate a DORA Article 26 TLPT scope document for a financial entity', a specific verb+resource. Sibling tools (list_phases, pricing, etc.) address different use cases, so this tool is well-distinguished.
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 context (generating a TLPT scope document) but does not explicitly state when to use this tool versus alternatives like pricing or threat_intel_brief. No exclusion criteria or guidance on when not to use it.
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:

[![csoai-dora-tlpt-planner-mcp MCP server](https://glama.ai/mcp/servers/CSOAI-ORG/csoai-dora-tlpt-planner-mcp/badges/card.svg)](https://glama.ai/mcp/servers/CSOAI-ORG/csoai-dora-tlpt-planner-mcp)

Score Badge

Copy to your README.md:

[![csoai-dora-tlpt-planner-mcp MCP server](https://glama.ai/mcp/servers/CSOAI-ORG/csoai-dora-tlpt-planner-mcp/badges/score.svg)](https://glama.ai/mcp/servers/CSOAI-ORG/csoai-dora-tlpt-planner-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/CSOAI-ORG/csoai-dora-tlpt-planner-mcp'

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