Task MCP Server
Server Quality Checklist
Latest release: v0.1.0
- Disambiguation5/5
Each tool has a clearly distinct purpose: add_task creates new tasks, complete_task updates task status, delete_task removes tasks, and list_tasks retrieves tasks. There is no overlap in functionality, making it easy for an agent to select the correct tool for any operation.
Naming Consistency5/5All tool names follow a consistent verb_noun pattern (add_task, complete_task, delete_task, list_tasks), using snake_case throughout. This predictability enhances usability and reduces confusion.
Tool Count5/5With 4 tools, this server is well-scoped for a task management domain, covering essential CRUD operations (create, read, update, delete) without unnecessary bloat. Each tool earns its place in the set.
Completeness5/5The tool surface provides complete CRUD/lifecycle coverage for task management: add_task (create), list_tasks (read), complete_task (update), and delete_task (delete). There are no obvious gaps, allowing agents to handle all core workflows without dead ends.
Average 2.5/5 across 4 of 4 tools scored.
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
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
Add a LICENSE file by following GitHub's guide. Once GitHub recognizes the license, the system will automatically detect it within a few hours.
If the license does not appear after some time, you can manually trigger a new scan using the MCP server admin interface.
MCP servers without a LICENSE cannot be installed.
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.jsonto 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
- Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It fails to indicate read-only safety, pagination behavior, return format, or scope constraints. The description provides zero behavioral context beyond the tool name.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5Is the description appropriately sized, front-loaded, and free of redundancy?
While brief (3 words), the description suffers from under-specification rather than effective conciseness. The single sentence fails to earn its place by adding value beyond the tool name, and lacks front-loaded critical context about behavioral safety.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, no annotations, and mutation-capable siblings, the description inadequately prepares the agent for tool selection. It omits critical context that this is a safe read operation and lacks any scope clarification necessary for an unparameterized list operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema contains zero parameters. Per rubric guidelines, 0 params establishes a baseline score of 4, as there are no parameter semantics to describe.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5Does the description clearly state what the tool does and how it differs from similar tools?
The description 'List all tasks' restates the tool name (tautology). While it confirms the action and resource, it fails to distinguish from siblings (add_task, complete_task, delete_task) or clarify scope (e.g., user-specific vs global tasks).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance provided on when to use this tool versus mutation alternatives (add_task, complete_task, delete_task). No mention of prerequisites or filtering limitations despite the 'all' scope implication.
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?
With no annotations provided, the description carries full disclosure burden. It states the tool is destructive ('Delete') but omits critical behavioral traits: whether deletion is permanent, recoverable, affects related data, or error cases (e.g., if task_id doesn't exist).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise (3 words), but this manifests as under-specification rather than efficiency. Given the tool's destructive nature and sibling ambiguity, the sentence fails to earn its place by omitting necessary context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a destructive operation with no annotations and no output schema, the description is incomplete. It lacks critical safety context (permanence, recovery options) and fails to clarify the distinction from 'complete_task', which is essential for correct agent selection.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% and adequately documents the single 'task_id' parameter. The description adds no additional semantic value beyond what the schema already provides, meeting the baseline for high-coverage schemas.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Delete a task' restates the tool name with minimal elaboration (tautology). While the verb and resource are clear, it fails to distinguish from sibling 'complete_task', which may also remove a task from active work but with different semantics.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides no guidance on when to use delete_task versus complete_task (permanent deletion vs. status change) or other alternatives. No prerequisites or conditions are mentioned.
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 provided, so description must carry full behavioral burden. It fails to disclose: return value (e.g., task ID), idempotency behavior, duplicate handling, or side effects. 'Add' implies mutation but lacks critical execution context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence with no redundancy, appropriately brief. However, brevity crosses into under-specification given lack of annotations and mutation behavior that requires disclosure.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Insufficient for a mutation tool with zero annotations and no output schema. Missing behavioral contract, sibling differentiation, and execution prerequisites that an agent needs to select and invoke correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% description coverage ('Task title', 'Task description'), meeting baseline expectations. Description text adds no parameter semantics beyond schema, but none are needed given complete schema documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Clear verb ('Add') + resource ('task') + scope ('to the task list'). States what the tool does without ambiguity. However, it does not explicitly distinguish from sibling 'complete_task' or clarify that this creates vs. modifies existing tasks.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides no guidance on when to use this tool versus siblings like 'complete_task' or 'delete_task'. No prerequisites, constraints, or conditions mentioned.
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?
With no annotations provided, the description carries the full disclosure burden. It implies a mutation (marking complete) but fails to specify idempotency, error conditions (e.g., invalid task_id), side effects, or whether the operation is reversible (can it be un-completed?).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely brief at four words with zero redundancy. While appropriately sized for a single-parameter tool, the extreme brevity contributes to the lack of behavioral and contextual detail found in other dimensions.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequate for a simple CRUD operation with full schema coverage and no output schema, but minimal given the absence of annotations. Lacks disclosure of error behaviors, return values, or side effects that would help an agent handle edge cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, establishing a baseline of 3. The description 'Mark a task as completed' implies the 'task_id' parameter refers to an existing task, but adds no syntax guidance, format constraints, or semantic context beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb ('Mark') and resource ('task') with clear state change ('as completed'). However, it does not explicitly differentiate from sibling tools (e.g., distinguishing an update operation from 'delete_task' or confirming behavior differs from 'add_task').
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides no guidance on when to use this tool versus alternatives, prerequisites for invocation (e.g., task must exist), or what happens if the task is already completed. Contains no 'when-not' or alternative recommendations.
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:
Score Badge
Copy to your README.md:
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
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/devirokkam/MCP_Github_Deployment'
If you have feedback or need assistance with the MCP directory API, please join our Discord server