personal-context-mcp

by KrystalJin1

Overview Schema Related Servers Score Discussions

Python

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Server Quality Checklist

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Latest release: v0.1.0
Disambiguation5/5
Each tool has a clearly distinct purpose: list_context shows board titles, get_context retrieves full content, search_context searches, who_am_i returns a compiled self-introduction, save_context writes/updates, and extract_file extracts text from files. No overlap.
Naming Consistency5/5
All tools use snake_case and follow a verb_noun pattern (list_context, get_context, search_context, save_context, extract_file), with who_am_i being a minor but acceptable variant. Very consistent.
Tool Count5/5
6 tools is well-scoped for a personal context server. It covers reading, writing, searching, file ingestion, and a summary tool without being too few or too many.
Completeness4/5
The tool set covers listing, reading, searching, creating/updating, and file extraction. A delete tool is missing, but the domain (personal context boards) may not require it. Minor gap, otherwise complete.
Average 3.4/5 across 6 of 6 tools scored. Lowest: 2.7/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 5 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
This repository is licensed under MIT License.
This repository includes a README.md file.
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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

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description only says '读取完整内容' (read complete content) but does not disclose permissions, auth needs, rate limits, or mutation effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise (one sentence) and front-loaded, but lacks structure and omits necessary details.
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?
Despite having output schema, description barely covers two parameters and lacks behavior explanation; insufficient for a tool with 1 required param.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%; description only mentions 'slug' indirectly but provides no meaning for 'viewer_tier'. Fails to add value beyond parameter names.
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 the verb '读取' (read), resource '板块完整内容' (section content), and references sibling tool for slug, distinguishing it from list_context and search_context.
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?
No explicit guidance on when to use get_context over siblings. Only implies slug from list_context but lacks conditions or alternatives.
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 the description must fully disclose behavioral traits. It mentions searching 'visible sections,' but fails to state read-only nature, authentication needs, rate limits, or any side effects. The operation's safety is unclear.
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, clear sentence with no unnecessary text. It front-loads the core verb and scope. A small deduction for being in Chinese, which may hinder non-Chinese agents, but the content is efficient.
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?
Given two parameters, no schema descriptions, no annotations, and an output schema not provided, the description is too sparse. It does not explain what 'visible sections' means, how results are sorted, or the role of 'viewer_tier'. The tool's behavior is underspecified.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description should explain parameters. It hints at 'query' via 'keyword search' but gives no details on format or constraints. The 'viewer_tier' parameter with default 'private' is completely ignored, leaving its meaning ambiguous.
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 action is keyword search across all visible sections, returning hit sections and context snippets. It distinguishes from siblings like list_context and get_context which list or retrieve specific contexts.
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?
No explicit guidance on when to use this tool versus alternatives such as list_context or get_context. The context of 'search' is implied but not contrasted with other listing/retrieval tools.
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?
The description discloses a key behavioral trait: it will overwrite a file with the same name. However, with no annotations provided, it lacks details about authentication needs, rate limits, or other side effects. The overwrite disclosure is useful but not comprehensive.
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 (two short sentences) and front-loads the action. It efficiently conveys the main purpose and usage context without unnecessary words.
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?
Given 5 parameters with no schema descriptions or annotations, the description is insufficient. It does not explain the output schema (though one exists) or cover parameter semantics. The tool's complexity demands more detail for an agent to use it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must explain parameters. It does not describe any of the five parameters (slug, title, body, tags, tier). The mention of 'section' is vague and does not map to parameter meanings. This leaves the agent with no guidance on how to fill parameters.
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 the action: 'write or update a section' and mentions overwriting, which is specific. It also provides a usage scenario ('after parsing resume/organizing experience'), distinguishing it from sibling tools like list_context, get_context, and search_context which are read-only.
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 gives a clear context for use ('after parsing resume/organizing experience, store the result into the knowledge base'), but it does not explicitly state when not to use or mention alternatives. However, the purpose is clear enough that an agent can infer appropriate usage relative to siblings.
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 burden. It discloses file types and the extraction-only behavior, but lacks details on error handling, size limits, or output format. The presence of an output schema reduces the need for return value details, but the description does not cover behavioral traits.
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 with two sentences, front-loading the main purpose. It is structured logically but could be slightly more organized.
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?
For a simple tool with one parameter and an output schema, the description covers core functionality and context. However, it lacks parameter details and behavioral aspects, leaving gaps for the agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% coverage with no parameter descriptions, and the description does not elaborate on the path parameter (e.g., format, constraints). Thus, it adds no value 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 the tool extracts plain text from pdf/docx/txt/md files, which is a specific verb+resource. It distinguishes from sibling tools like save_context by explaining it is a preliminary step.
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 context on when to use the tool as the first step before save_context, and clarifies that optimization is left to AI. However, it does not explicitly exclude alternative scenarios.
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 discloses that the tool returns all visible content under a tier, implying a read operation, but lacks details on permissions, what 'visible' means, or whether the operation is expensive. Some transparency but insufficient depth.
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 consists of two short, direct sentences with no wasted words. It is front-loaded with the core purpose and immediately clarifies when to use the tool.
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 and the existence of an output schema, the description is fairly complete. It explains the overall purpose and the parameter's role, though it could briefly mention what 'all visible content' entails. Still, it is adequate for a straightforward tool.
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?
With 0% schema description coverage, the description partially explains the 'viewer_tier' parameter by mentioning '该 tier', indicating it controls which tier's content is included. However, it does not explain possible values or the default behavior, adding some but not complete meaning.
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 returns a complete self-introduction composed of all visible content under a specified tier. The verb '返回' and resource '自我介绍' are specific, and it distinguishes from sibling tools that handle individual context operations.
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 a clear use case: when switching to a new AI, call this tool to help it know you. It does not explicitly exclude alternative uses or compare to siblings, but the context is clear.
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 weight. It discloses that the tool lists 'visible' boards filtered by viewer_tier, which is a key behavioral trait. It does not explicitly state that the operation is read-only, but '列表' (list) implies no side effects. The presence of an output schema compensates for not detailing the return format.
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 composed of two concise sentences. The first sentence states the core purpose and output fields. The second sentence explains the parameter. Every word adds value, and the key information is front-loaded.
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 presence of an output schema, the description adequately covers the tool's purpose and parameter. It is complete enough for a listing tool with a single optional parameter. It does not mention pagination or ordering, but these are not critical for basic usage; the output schema likely handles structure.
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 description adds significant meaning to the viewer_tier parameter beyond the schema. It lists the allowed values (public/recruiter/friend/private) and explains that it determines visibility. The schema only defines it as a string with a default, so the description is essential for correct usage.
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 specifies the verb '列表' (list) and the resource '个人上下文板块' (personal context boards), clearly indicating the tool's function. It also explicitly mentions the fields returned (title, slug, tier, tags). This distinguishes it from siblings like get_context (likely single item retrieval) and search_context (searching).
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 explains the viewer_tier parameter and its effect on visibility, which gives usage context. However, it does not state when to use this tool versus alternatives like get_context or search_context, nor does it provide when-not-to-use hints. Sibling names are only available through context signals, not in the description.
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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