Deepseek Thinker MCP Server
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
With only one tool, there is no possibility of ambiguity or overlap between tools. The single tool's purpose is clearly distinct by default.
Naming Consistency5/5The single tool name 'get-deepseek-thinker' follows a consistent pattern, and with no other tools to compare, there is no inconsistency in naming conventions.
Tool Count2/5A single tool is too few for most server purposes, as it limits functionality and suggests a thin or incomplete surface. This is borderline for typical server scopes, leaning towards inadequacy.
Completeness1/5The server's purpose appears to be 'think with deepseek,' but with only one tool, the surface is severely incomplete. There are obvious gaps, such as no way to configure, modify, or manage thinking processes, leading to dead ends for agents.
Average 1.7/5 across 1 of 1 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- 0 of 1 community issues answered or closed 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
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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 full burden for behavioral disclosure. 'think with deepseek' reveals nothing about whether this is a read/write operation, what permissions are needed, whether it has side effects, rate limits, or what kind of response to expect. It's completely opaque about behavioral characteristics.
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 technically concise with just three words, this is under-specification rather than effective conciseness. The description fails to convey meaningful information, so its brevity is a deficiency rather than a virtue. Every word should earn its place, but here the words don't provide useful content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no annotations and no output schema, the description is completely inadequate. It doesn't explain what the tool does, when to use it, what behavior to expect, or what results it returns. The single parameter is documented in the schema, but the overall context for using this tool is missing entirely.
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%, with the single parameter 'originPrompt' clearly documented as 'user's original prompt'. The description adds no additional parameter information beyond what the schema provides, which is acceptable given the high schema coverage. The baseline of 3 is appropriate when the schema does the documentation work.
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 'think with deepseek' is a tautology that restates the tool name rather than explaining what the tool actually does. It doesn't specify what resource is being accessed or what operation is performed. While it hints at some thinking/processing function, the purpose remains vague and undefined.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides absolutely no guidance about when to use this tool, what problems it solves, or what context it's appropriate for. There are no sibling tools mentioned, but even for a standalone tool, this offers no usage context or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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