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Server Details
Snagging Software: the site's own MCP server — compare, enquiry (enquiry = a human handoff, not...
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
Available Tools
6 toolscompare_criteriaWhat is comparedBInspect
The criteria and any filters of the Snagging and defect management systems used by UK housebuilders and contractors comparison.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
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 offers topical scope (UK housebuilders/contractors, snagging and defect management) but never states what the tool actually does—whether it returns a list, performs a lookup, or has side effects. The missing verb leaves behavior largely unspecified.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and contains no filler, but it is grammatically awkward and reads like a heading fragment rather than a well-formed definition. A single clear verb-first sentence would be more effective.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a parameterless tool, the description gives a workable hint about the content—criteria and filters—and a specific domain scope. However, with no output schema and no stated action, an agent still lacks a definitive statement of what the tool returns or how to use it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters and the schema is an empty object, so schema coverage is effectively complete. There are no parameter semantics that the description needs to clarify.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description identifies a specific resource—criteria and filters for comparing UK housebuilders' snagging and defect management systems—and implicitly differentiates it from siblings like compare_options and compare_table. However, it is a noun phrase with no main verb, so the actual operation of the tool must be inferred rather than stated.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no explicit guidance on when to use this tool versus compare_options or compare_table. The description implies it is relevant when comparison criteria or filters are needed, but it does not state conditions, prerequisites, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
compare_optionsThe optionsCInspect
The options in the Snagging and defect management systems used by UK housebuilders and contractors comparison (name, what it is best for, tags), optionally filtered by a tag value.
| Name | Required | Description | Default |
|---|---|---|---|
| filterKey | No | ||
| filterValue | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of disclosing behavior. It mentions comparison and optional filtering, but does not disclose whether the operation is read-only, whether any side effects occur, what the return format is, or any access requirements.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is only one sentence but is awkwardly structured and reads like a fragment ('...systems comparison...'). It is not front-loaded clearly, and the title 'The options' is unhelpful. A clearer, more direct rewrite would earn a higher score.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no annotations, the description should explain return contents and calling context more fully. It lists comparison fields and a filter option, but leaves filterKey semantics unclear and does not describe the result format or any limitations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must explain the parameters. It mentions 'filtered by a tag value,' which likely relates to filterValue, but it does not explain filterKey or how the two parameters interact. The parameter semantics are incomplete.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description identifies the resource as 'options' in UK housebuilding snagging/defect management systems and indicates a comparison function with fields (name, best for, tags). This is distinguishable from siblings like compare_criteria and compare_table, though the phrasing is malformed and the title 'The options' adds nothing.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when comparing options and mentions optional filtering by tag value, but it gives no explicit guidance about when to choose this tool over compare_criteria or compare_table. No alternatives are named or excluded.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
compare_tableThe comparison tableCInspect
Each option's value on every criterion of the Snagging and defect management systems used by UK housebuilders and contractors comparison — the full table.
| Name | Required | Description | Default |
|---|---|---|---|
| option | No | one option's name, else all |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure, but it only restates the output content. It does not mention whether the operation is read-only, how supplying or omitting the 'option' parameter changes the result, what shape the returned data takes, or any other behavioral traits beyond the literal content.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The text is short, but the single sentence is grammatically tangled ('...systems used by UK housebuilders and contractors comparison — the full table'), which impairs readability. The key idea (full table of all options vs criteria) is embedded awkwardly at the end rather than being cleanly front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Although the tool is simple (one optional parameter, no output schema, no nested objects), the description omits any relation to sibling tools and conveys its purpose in confusing phrasing. An agent cannot reliably decide between this and compare_options or compare_criteria without inspecting their schemas, and the return value is only vaguely described.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% — the only parameter 'option' is already fully described as 'one option's name, else all.' The description adds nothing about the parameter's effect on the output, so the baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description identifies the resource (the comparison table of snagging and defect management systems) and what it contains (each option's value on every criterion), which clearly distinguishes it from the narrower sibling views compare_criteria and compare_options. However, the grammar is convoluted and there is no explicit verb stating what the tool does, so it reads more like a data label than a behavioral definition.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given about when to use this tool versus its siblings. 'The full table' weakly implies it is the comprehensive view compared to compare_criteria and compare_options, but those alternatives are never named and no selection logic or exclusion criteria are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
enquiry_describeWhat you get: an ENQUIRY with a human (not a purchase, not a guaranteed quote)AInspect
Read first. States plainly what submit_enquiry does on Snagging Software: it starts an enquiry with human providers who quote directly. Nothing is bought, ordered or paid; no quote is guaranteed; it is free. Also returns who receives the details, the consent wording, and how the person confirms.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It explicitly says nothing is bought, ordered, or paid and that the process is free, which clarifies non-transactional behavior. It also describes what the tool returns: who receives details, consent wording, and confirmation method. This is sufficient for a no-parameter read-only informational tool, though it does not discuss auth or rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with 'Read first' and delivers the core purpose early. It is slightly wordy with redundant emphasis on 'nothing is bought, ordered or paid' and 'free', but every sentence contributes to preventing misuse. It remains appropriately sized for a no-parameter tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a no-parameter tool with no output schema, the description gives enough detail about its informational role and return content. It names the related submit_enquiry flow and explains the key behavioral caveats. It could add a little more about when not to use it relative to comparison tools, but it is largely complete for its simple purpose.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so parameter semantics are trivially satisfied; the baseline for 0 parameters is 4. The description confirms there is no input required by framing the tool as a 'read first' reference. No additional parameter explanation is needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a precise purpose: it explains what submit_enquiry does on Snagging Software, distinguishing this informational tool from the action tool itself. It clearly defines scope by noting nothing is purchased, ordered, or paid, and that no quote is guaranteed. The 'Also returns...' clause specifies concrete output content, making the tool's function unmistakable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The opening 'Read first' directly tells an agent to use this tool before proceeding, which is clear when-to-use guidance. It contrasts with submit_enquiry by explaining that this tool does not create a purchase or guaranteed quote, helping avoid misuse. It does not name alternative sibling tools such as compare_criteria, but the context makes the primary usage scenario obvious.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
enquiry_fieldsThe questions the enquiry asksAInspect
Every field of the Snagging Software enquiry: key, label, type, whether required, help text and the allowed options where there are any. Pass answers to submit_enquiry keyed by field key.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses what data the tool returns and ties it to the submission flow. It does not explicitly state side-effect safety or read-only behavior, but the semantics of listing fields strongly imply a non-mutating metadata lookup, and the absence of parameters supports this.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no filler. The first sentence front-loads the full inventory of returned content; the second connects the tool to its sister tool with a specific instruction. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple: no parameters, no output schema, no annotations. The description explains what fields are returned and how to use them with submit_enquiry. It could be marginally more explicit about return format or read-only behavior, but given the low complexity, it is substantially complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the baseline is 4. The description adds relevant context about how the returned keys are used with submit_enquiry, even though there are no parameters to explain.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly indicates the tool provides all fields of the Snagging Software enquiry, listing the exact attributes (key, label, type, required, help text, allowed options). The verb is implicit rather than explicit ('Every field…' rather than 'Returns every field'), and it does not directly differentiate from enquiry_describe, but the resource and content are unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives actionable context: pass answers to submit_enquiry keyed by field key, which tells an agent when this tool is relevant (preparing a submission). It does not explicitly name alternatives or exclusion conditions, but the use case is clear enough for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
submit_enquirySubmit an ENQUIRY to human providers (two steps; not a purchase)AInspect
Submits an enquiry to Snagging Software — NOT a purchase, NOT a guaranteed quote. Step 1: call with the answers (keyed by field key from enquiry_fields) and consent=true; it validates and returns a summary, the consent line and a confirmation token — show the person the summary and the consent line. Step 2: only if the person agrees, call again with the same answers, consent=true and the confirmation token; the enquiry is then submitted, and the person receives an email with a link they must click before any provider sees it. Consent means the person has read and agreed to: "Happy for my details to go to a snagging software supplier, who'll contact me directly."
| Name | Required | Description | Default |
|---|---|---|---|
| answers | Yes | the person's answers, keyed by field key | |
| consent | Yes | true only when the person has agreed to: Happy for my details to go to a snagging software supplier, who'll contact me directly. | |
| confirmation | No | the confirmation token from step 1, after the person has approved the summary |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden and does so excellently. It discloses the two-step side-effect behavior, that the enquiry is not final until the second call, that an email with a clickable link is sent, and that providers only see the enquiry after the click. It also states the exact consent wording, making behavioral expectations 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is long but every sentence earns its place; it packs critical protocol, consent text, and provider-visibility behavior into one dense paragraph. It could be slightly improved with bullet-like separation of steps, but the numbered markers keep it readable and front-loaded with the most important caveat.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a complex two-step tool with nested objects and no output schema, the description is remarkably complete. It explains all three parameters' roles, the step-1 return values, the step-2 condition, and the post-submission email flow. An agent has enough context to execute the full protocol correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Although schema coverage is 100%, the description adds substantial meaning beyond the schema: answers are keyed by field key from enquiry_fields, consent must match an exact agreement line, and confirmation is the token returned from step 1. This turns bare parameter names into a usable workflow.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool 'Submits an enquiry to Snagging Software' and immediately distinguishes it from a purchase or guaranteed quote. This precise verb+resource framing and the explicit 'not a purchase' clarification prevents confusion with the sibling comparison and enquiry-description tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives an explicit two-step invocation protocol: call with answers and consent=true, receive a summary and token, then call again with the same data plus token after person approval. It also specifies the consent requirement verbatim and when the enquiry becomes visible to providers, leaving no ambiguity about when and how to use the tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
6 tool updates
- First observed
compare_criteria - First observed
compare_options - First observed
compare_table - First observed
enquiry_describe - First observed
enquiry_fields - First observed
submit_enquiry
Frequently Asked Questions
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/.well-known/glama.jsonon the same origin as the connector, then choose Check HTTP challenge.DNS challenge — works when you control DNS but cannot change the server. Generate a token, create the exact TXT record Glama shows, wait for it to propagate, then choose Check DNS challenge.
After verification, Glama sends a confirmation email and gives you access to listing details, thumbnails, health checks, and analytics. Keep the HTTP file or DNS record in place: Glama periodically checks it and ownership remains verified while the token is discoverable.
The HTTP ownership file has this structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"claim": "glama_claim_..."
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For a connector linked to the official MCP Registry, registry updates continue to replace its name, description, and URL by default. After claiming, open Manage connector and enable Use Glama listing details as the source of truth if edits made on Glama should be preserved. Categories and thumbnails are always managed on Glama; registry linkage and technical connection settings continue to sync.
Control your server's listing on Glama, including description and metadata
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To improve your MCP server's ranking:
Claim ownership of the server listing
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Provide a test profile so Glama can connect to and evaluate the server
Keep tool definitions clear and complete to earn a high Tool Definition Quality Score (TDQS)
Route real usage through the Glama Gateway; more recorded successful server uses also improve the ranking
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Full audit trail – every tool call is logged with inputs and outputs for compliance and debugging
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For server owners:
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Tool-level analytics – see which tools are being used most, helping you prioritize development and documentation
Direct user feedback – users can report issues and suggest improvements through the listing, giving you a channel you would not have otherwise
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TDQS
Each tool has a clear, distinct role: comparison tools separate criteria, options, and the full table, while enquiry tools separate explanation, fields, and submission. There is no meaningful overlap between any two tools.
Tool names consistently use snake_case, but the pattern is mixed: compare_* tools are verb-first, enquiry_describe and enquiry_fields are noun-first, and submit_enquiry is verb-first. The names are readable and grouped by domain, but the convention is not fully uniform.
Six tools is well-scoped for this site: three comparison tools cover the comparison table experience, and three enquiry tools cover the enquiry flow. Each tool earns its place with no redundant or excessive additions.
The tool surface covers the full apparent purpose: comparing snagging and defect management systems and submitting an enquiry. The enquiry flow is complete with describe, fields, and two-step submission, leaving no obvious dead ends.