Ionic Framework MCP Server
Server Quality Checklist
Latest release: v0.0.1
- Disambiguation5/5
Each tool has a clearly scoped responsibility: discover components, read usage examples, search docs, read full pages, and fetch blog posts. Descriptions explicitly direct the agent to the correct tool for adjacent tasks, so there is little chance of misselection.
Naming Consistency5/5All tool names follow a consistent snake_case verb_noun pattern: list_*, get_*, search_*. The names are predictable and readable, with only minor variation in object naming that does not hurt consistency.
Tool Count5/5Five tools is a well-scoped size for a documentation-focused MCP server. Each tool earns its place and covers a distinct user need without redundancy or obvious missing pieces.
Completeness5/5The tool set covers the full documentation workflow: discovering components, searching documentation, reading full pages with API references, and inspecting framework-specific usage. Search results and component listings provide URLs that feed directly into get_doc_page, so there are no dead ends.
Average 4.9/5 across 5 of 5 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- No commit activity data available
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
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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
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already establish readOnly/openWorld/non-destructive behavior. The description adds meaningful context beyond annotations: the 10-post limit, the fact that the blog covers both Ionic Framework and Capacitor, and that the feed only carries the newest posts. It does not go into depth on rate limits or pagination, but that is minor given the safety profile is already covered.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Four sentences with no wasted words. The main action is front-loaded, followed by usage context, returned fields, and an explicit when-not-to-use with an alternative. Every sentence adds distinct value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter read-only tool with no output schema, the description is fully adequate: it explains what the tool does, when to use it, what it returns, and when to avoid it. An agent can invoke it correctly without any additional information.
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?
There are zero parameters and the schema coverage is 100%, so the schema leaves nothing to clarify. The description adds no parameter details, but none are needed; per the rubric a zero-parameter tool earns a baseline of 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific action ('List'), a precise resource ('the 10 most recent posts from the official Ionic blog'), and an ordering ('newest first'). It clearly differentiates from sibling documentation tools by framing this as a blog/announcement feed rather than a documentation resource.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is explicitly conditioned on 'when the question is about what is new — recent releases, announcements or deprecations.' It also names a specific exclusion (documentation questions) and directs to the alternative sibling 'search_docs'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark it read-only and non-destructive; the description adds the behavior that matters for calling: two call modes (list examples vs. return code), the return structure (fenced code blocks, one section per framework, one block per file for multi-file examples), and framework filtering. This is substantive disclosure beyond the readOnlyHint.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Five sentences with no filler, logically ordered: what → when → how → return format → explicit exclusion. The purpose is front-loaded in the first sentence, and every clause earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Without an output schema, the description carries the burden of explaining return values and does so in detail (frameworks per example, fenced blocks, multi-file handling). Combined with 100% schema coverage and readOnly annotations, an agent has everything needed to call this correctly.
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?
Schema coverage is 100% and each parameter is individually well-described, so the baseline is 3. The description adds above-baseline value by wiring the parameters into a workflow — 'Call it without an `example` first to see which examples the component offers' — and by clarifying what the returned code contains (template, component class, styles).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb and resource — 'Read the official usage examples of one Ionic Framework component' — and explicitly differentiates from a sibling: 'Do not use this for the component's API reference... which get_doc_page returns.' An agent can tell exactly what this does and what it is not for.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Gives explicit when-to-use ('Use this before writing markup for a component'), an explicit workflow ('Call it without an `example` first'), and an explicit when-not with the named alternative ('Do not use this for the component's API reference... which get_doc_page returns'). Nothing is left to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark this readOnlyHint=true and destructiveHint=false, and the description adds meaningful behavioral context beyond that: it returns best-matching page sections with specific fields, attaches results as structured content, and warns that guessing component properties or CSS variables produces silently broken markup. It also clarifies that the tool does not read whole pages, setting correct expectations for the result granularity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is dense but every clause earns its place: purpose, scope, return shape, structured-content note, and routing to alternatives are all included. The first sentence immediately states the verb and resource, and the exclusions are batched at the end. No filler or repetition of the schema is present.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's search behavior, rich schema, output schema, and sibling tools, the description covers everything an agent needs: what it searches, what it returns, how results should be used, and when to select a different MCP server or sibling tool. No critical operational or contextual gap remains.
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?
Schema coverage is 100%, so the baseline is 3. The description adds value by explaining the query behavior ('by keyword', 'best matching page sections') and explicitly directing agents to use returned urls with get_doc_page. It also reinforces that plain keywords work best and the tool returns structured content, which helps an agent form better queries beyond what the schema alone states.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific action ('Search the official Ionic Framework documentation from ionicframework.com by keyword') and enumerates the exact topics it covers, from UI components to migrations. It also clearly distinguishes itself from get_doc_page by specifying that search_docs returns page sections rather than whole pages. This is a precise, resource-specific purpose statement.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says to use this tool first for any Ionic Framework question, and gives concrete exclusion cases: use get_doc_page for reading a full page, the Capacitor MCP server for Capacitor/native concerns, and the Capawesome MCP server for Capawesome Cloud services. This is model guidance with named alternatives and clear routing conditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The readOnlyHint and openWorldHint annotations already indicate safety, and the description goes further by specifying that the whole page is returned, anchors are ignored, and the output includes page title, URL, version, and markdown. This provides concrete behavioral expectations beyond the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the primary purpose and every sentence serves a distinct role: purpose, usage relationship, output details, and exclusion rules. It is slightly verbose but not redundant, and each sentence adds necessary guidance.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having no output schema, the description explicitly lists what will be returned, making the tool fully understandable. It also covers version defaults, URL formats, and exclusion boundaries, so an agent has all necessary context to invoke it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already covers required and optional parameters, but the description adds meaningful context: URL examples, the fact that anchors are ignored, and that the version defaults to v9 and should match the user's package.json. This goes well beyond the raw schema information.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool reads the full markdown of a single page of the official Ionic Framework documentation. It also distinguishes itself from sibling tools by explicitly saying to use it after search_docs to read a page rather than to find one.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit when-to-use guidance: after search_docs and before writing markup against a component. It also gives clear when-not-to-use instructions, including not to find a page and not to use it for pages outside ionicframework.com.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the readOnlyHint annotation, the description reveals the exact return fields (tag, description, url) and the semantic of url as the doc page, and clarifies that limit 100 retrieves every component.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is tight, direct, and logically organized into a purpose, a use case, return format, and explicit exclusions—no fluff or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Even without an output schema, the description sufficiently explains what will be returned and how it links to the documentation, making it fully actionable in context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Though schema descriptions already cover all parameters, the description adds actionable guidance like 'Use limit 100 to list every component' and the instruction to match the version to the user's package.json, enriching parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it lists Ionic Framework UI components with optional keyword filtering, and explicitly distinguishes from sibling tools by directing API reads to get_doc_page and Capacitor plugins to another server.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit when-to-use guidance ('find the component that fits a piece of UI... learn the custom element name') and when-not-to-use guidance ('Do not use this to read a component's API... Do not use it for Capacitor plugins').
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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- Confirm that the MCP server is working as expected.
- Confirm that there are no obvious security issues.
- Evaluate tool definition quality.
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