SummitFlow MCP

Server Quality Checklist

Profile completionA complete profile improves this server's visibility in search results.

Latest release: v0.1.0
Disambiguation5/5
Each tool has a clearly distinct purpose: date calculations (federal_holidays, business_days_between, add_business_days), planning (grant_deadline_plan), budgeting (grant_budget), valuation (volunteer_time_value, in_kind_value), reference (grant_lead_times, summitflow_resources). Even the date-related tools are complementary: listing holidays, counting business days, and adding business days serve different needs. No two tools appear to do the same thing.
Naming Consistency4/5
All tool names follow a consistent lowercase-with-underscores style and are descriptive. However, the grammatical pattern is not uniform: some are verb phrases (add_business_days) while others are noun phrases (business_days_between, volunteer_time_value). This minor inconsistency keeps it from a 5, but the overall naming is predictable and readable.
Tool Count5/5
With 9 tools, the server is well-scoped for its purpose. Each tool addresses a distinct aspect of grant planning—deadlines, budgets, match valuation, and reference materials—without unnecessary redundancy. This is within the ideal 3-15 range and feels comprehensive without being bloated.
Completeness4/5
The core grant planning workflow is well covered: date calculations, deadline planning, budget construction, and volunteer/in-kind valuation. A possible gap is the lack of tools for more advanced grant management tasks like tracking submitted applications or generating budget narratives, but the existing tools form a coherent set for the stated purpose. The inclusion of a resources tool helps round out the surface.
Average 3.7/5 across 9 of 9 tools scored. Lowest: 2.1/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 2 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?
With no annotations provided, the description carries the full burden of disclosing behavior. It only states the content type ('templates, guides and calculators') and location ('on the web') but fails to mention whether this is a live fetch, a static list, how results are returned, or any network dependencies. The agent is left with no behavioral insight.
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?
The description is very concise, but it is under-specified. It is a single sentence without a verb or clear structure. While brevity is positive, it borders on a label rather than a functional description, so it does not fully earn its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has an output schema but no annotation context. The description does not explain what the tool returns or how the output relates to the mentioned templates/guides/calculators. For a resource tool, the agent needs to know whether the output is a list of links, metadata, or downloadable files, but this is entirely absent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, and the schema is empty. Per the rubric, a baseline of 4 is appropriate for zero-parameter tools. The description correctly does not attempt to explain parameters since there are none.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Free grant templates, guides and calculators on the web' is a noun phrase without an explicit verb or action. It hints at the resource type but does not clearly state what the tool does (e.g., lists, retrieves, or provides these items). It is not a tautology but lacks a specific functional purpose.
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?
The description provides no guidance on when to use this tool versus the sibling tools (e.g., grant_budget, volunteer_time_value). There is no mention of use cases, prerequisites, or alternatives, leaving the agent to infer applicability.
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, the description carries the full burden. It discloses that the output includes lead times and reasoning, which is some behavioral detail, but it does not mention side effects, authentication needs, rate limits, or what kind of data is returned. The description adds minimal transparency beyond the mere existence of the tool.
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, concise sentence that front-loads the core subject (lead times) and adds a helpful qualifier (with reasoning). It is not verbose, but the lack of a verb makes it slightly cryptic. Still, it earns its place and is appropriately sized.
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?
Although an output schema exists, the description provides only a hint of the tool's function by referencing grant_deadline_plan. For a tool with no parameters, this might suffice, but it does not explain what 'lead times' mean in this context or how this relates to other siblings. The description is minimally complete but leaves room for ambiguity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, and the schema description coverage is 100% (vacuously). The baseline for zero parameters is 4, and the description does not need to add parameter details. The mention of lead times and reasoning is sufficient given there are no inputs to clarify.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'The lead times behind grant_deadline_plan, with the reasoning for each' clarifies the tool's subject matter by referencing grant_deadline_plan, but it lacks an explicit verb (e.g., 'retrieve', 'get'). It distinguishes the tool from siblings by indicating it provides lead times and reasoning, but the purpose is not stated as an actionable operation.
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 guidance is given on when to use this tool versus alternatives. The reference to grant_deadline_plan implies it relates to that sibling, but it never states when this tool should be preferred or excluded. There is no mention of context, prerequisites, 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 are provided, so the description carries full burden. It mentions required item fields but does not disclose the calculation behavior (e.g., summing fair_market_value * quantity), error handling, or whether extra item properties are ignored. This is insufficient for a mutation/calculation tool with no annotation safety profile.
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 two sentences, front-loaded with the purpose in the first phrase, and the parameter requirements follow. Every sentence provides value without redundancy or filler.
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?
The description covers the input structure but omits the core calculation logic (how fair_market_value and quantity are combined) and error behavior. While an output schema exists, the missing computation detail leaves a gap for a simple tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides only an 'items' array of empty objects (0% coverage). The description compensates by specifying that each item needs 'description' and 'fair_market_value' and optional 'quantity' with default 1. This adds crucial meaning beyond the schema, though it omits types/formats.
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 'Total donated goods and services' clearly identifies the resource (donated goods/services) and the purpose (calculating a total), distinguishing it from siblings like volunteer_time_value. While the verb is implied rather than explicit ('Calculate total...'), it is still understandable and specific.
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 implies usage by stating the required fields ('description', 'fair_market_value') and optional 'quantity', so the agent knows when to use it. However, it does not provide explicit guidance on when to prefer this tool over alternatives like volunteer_time_value or mention any exclusions.
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 key behavior (skipping weekends and US federal holidays) and supports negative numbers for subtraction. However, it does not mention edge cases like start_date falling on a weekend/holiday, date format expectations, or output details.
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 a single concise sentence that front-loads the core action and constraints. Every phrase adds value ('skip weekends and US federal holidays', 'negative number') without waste.
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?
The tool is simple but still lacks details about input date format, behavior when start_date is a non-business day, and output schema specifics. With no annotations and minimal parameter guidance, the description is adequate but not complete for a production tool.
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?
The schema provides only types (string, integer) with 0% coverage from the description. The description only hints that 'days' can be negative but does not clarify the expected date format (e.g., YYYY-MM-DD) or the semantics of 'days' beyond business-day count. This is insufficient compensation for the lack of schema descriptions.
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 uses a specific verb ('Add') with a clear resource ('business days to a date') and specifies scope ('skipping weekends and US federal holidays'). It clearly distinguishes itself from siblings like business_days_between and federal_holidays.
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 states the operation (add/subtract business days) but does not explicitly mention when to prefer this over alternatives. The existence of sibling tools like business_days_between suggests different use cases, but no direct comparison or exclusion is given.
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?
With no annotations, the description carries the full burden of behavioral disclosure. It clearly states that weekends and US federal holidays are skipped and that dates must be ISO format. However, it does not mention edge cases like whether endpoints are inclusive or what happens when start_date > end_date, leaving some ambiguity.
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 two sentences, both of which are informative. The first sentence states the core purpose and behavior, the second provides the necessary date format detail. No wasted words.
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 presence of an output schema, the description covers the essential aspects: purpose, holiday handling, and date format. The main gap is the lack of specification about endpoint inclusivity or behavior on invalid date ranges, but overall it is reasonably complete for a business-day counter.
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?
The schema coverage is 0%, so the description must compensate. It adds that dates are in ISO format (YYYY-MM-DD), which applies to both parameters, but it does not explain the individual parameter roles beyond their self-explanatory names (start_date, end_date). Since the names are clear and the format note is useful, a score of 3 reflects partial compensation.
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 counts business days between two dates, with the specific behavior of skipping weekends and US federal holidays. This distinguishes it from siblings like add_business_days (which adds days) and federal_holidays (which lists holidays), making the purpose unambiguous.
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 usage is implied: use this tool when you need to count business days between two dates. However, there is no explicit guidance about when not to use it or alternatives (e.g., 'use add_business_days for adding days'). Given the sibling tools, more explicit differentiation would help.
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?
With no annotations provided, the description carries the full burden. It discloses the default behavior (published national rate) and explains the skilled-volunteer exception, which is critical behavioral context. It does not describe the return format, but the presence of an output schema likely covers that.
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 two sentences long, front-loaded with the primary purpose, and includes only necessary behavioral guidance. Every phrase earns its place with no redundancy or filler.
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 simple nature (3 params, no nested objects, output schema present), the description covers the core purpose, default behavior, and a key edge case. It omits details like return currency or total-hours calculation, but these are either inferable or handled by the output schema.
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?
Schema description coverage is 0%, so the description must compensate. It adds meaning to the hourly_rate parameter by explaining the default national rate and the skilled-volunteer override, but it does not explicitly map these behaviors to parameter names. The hours and volunteers parameters are self-explanatory from their schema definitions.
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 opens with 'Value volunteer time for match requirements or an annual report,' which uses a specific verb ('value') and resource ('volunteer time') while stating the use case. This clearly distinguishes it from sibling tools like in_kind_value, which likely handles broader in-kind donations.
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 explicit contexts ('match requirements or an annual report') and a specific usage scenario for skilled volunteers (legal, accounting, medical). However, it does not mention alternatives or when not to use the tool, so it lacks explicit exclusions.
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?
With no annotations, the description carries the burden of disclosing behavior. It explains that the tool returns observed dates and explains the rule for Saturday holidays. While it doesn't detail edge cases like year range or data source, the key behavioral trait is well covered.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long, with the main purpose front-loaded and the nuance about observed dates in a concise second sentence. Every word earns its place; there is no fluff or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple (one parameter) and an output schema exists, so the description need not elaborate on return values. It provides enough context for an agent to decide when to use it and what to expect, making it complete for its complexity.
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?
Schema description coverage is 0%, so the description must compensate for the 'year' parameter. It does clarify that the year is the target year for holidays, but it does not specify valid ranges, formats, or constraints. This is acceptable but not comprehensive.
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 lists US federal holidays for a given year, with a specific verb ('List') and resource ('federal holidays'). It distinguishes itself from siblings like business_days_between and add_business_days by focusing on holiday enumeration rather than date arithmetic.
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?
It provides clear context by explaining that observed dates matter for deadlines (e.g., Saturday holidays close offices Friday). However, it does not explicitly name alternative tools or state when not to use this tool, so it stops short of full when/when-not guidance.
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?
With no annotations provided, the description carries the full burden. It discloses the core behavior—calculating on the correct base—and explains the exact meaning of MTDC (excludes equipment and subaward amounts above $25k). It also warns about the inflationary effect of using the wrong base. It doesn't detail output structure, but the presence of an output schema hints that is covered elsewhere.
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 tight: three sentences that lead with the main purpose, then explain the key parameter, and end with a valuable warning. No filler or redundant information.
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 9 optional parameters, no annotations, and an output schema (not shown), the description covers the most important decision—indirect_base—and the calculation logic. It doesn't elaborate on the exact output format or the relationship between fringe and personnel, but the output schema likely provides those details. It is sufficient for an agent to invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero descriptions, so the description compensates by fully explaining indirect_base and its allowed values ('mtdc'/'tdc'). Other parameters like travel, supplies, personnel, and rates are self-explanatory from their names. This addresses the only ambiguous parameter.
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 opens with 'Build a grant budget with fringe and indirect calculated on the correct base,' using a specific verb and resource. It clearly distinguishes this tool from siblings like grant_deadline_plan or business_days_between, which serve different grant-related purposes.
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?
It provides clear context for when to use the tool (building grant budgets) and offers critical guidance on selecting indirect_base, including the difference between MTDC and TDC and the common pitfall of using total direct costs. It does not explicitly exclude other tools, but none are budget calculators, so the use case 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?
With no annotations provided, the description carries the full burden. It discloses that weekends and federal holidays are automatically handled, and it lists the three return milestones. This gives a clear picture of behavior without needing the tool to be invoked. The absence of any mention of side effects or permissions is acceptable for a calculation tool, but it does not specify how invalid dates are handled, so a slight deduction.
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 concise, with the main purpose in the first sentence, followed by a compelling one-liner ('A deadline is not a plan.') and a clear explanation of outputs. The parameter documentation is included inline without unnecessary verbosity. Every sentence adds value.
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 that an output schema exists, the description does not need to detail return structures. It covers the core behavior, including holiday handling, and provides parameter guidance. It could mention edge cases like past deadlines or formatting requirements, but for a tool of this complexity it is nearly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema provides no descriptions, but the description compensates by explaining that 'deadline' is the funder deadline and by enumerating valid values for 'application_type' (loi, proposal_new, proposal_renewal, federal, report). While the date format for 'deadline' is not specified, the parameter name and context are clear enough.
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's function: 'Work backward from a funder deadline to the dates that actually matter.' It specifies the exact outputs (start drafting, internal review copy due, packet complete) and differentiates itself from sibling tools by focusing on planning rather than simple date arithmetic or resource valuation.
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 clearly implies when to use this tool: whenever a user has a funder deadline and needs to determine actionable internal milestones. It does not explicitly exclude alternative tools like 'business_days_between' or 'add_business_days', but the context is strong enough that an agent would likely select it appropriately. A small deduction for not stating when not to use it.
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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