@propraven/mcp

by jdw2111

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Server Quality Checklist

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Latest release: v0.1.1
Disambiguation5/5
Each tool has a clearly distinct purpose: parcel.lookup for single parcel, parcel.search for filtering, parcel.compare for ranking multiple, owner.pierce for portfolio, hazard.score for risk, valuation.estimate for value, permits.history for construction, sales.history for transactions. No overlaps.
Naming Consistency5/5
All tools use a consistent 'domain.action' pattern with lowercase and underscores (e.g., parcel.lookup, parcel.search, owner.pierce). The verb or noun after the dot is descriptive and follows a clear taxonomy.
Tool Count5/5
8 tools is well-scoped for a property intelligence server. Covers core operations (lookup, search, compare), ownership, risk, valuation, permits, and sales without excessive granularity.
Completeness4/5
Covers most key workflows: parcel identification, search, comparison, owner research, hazard, valuation, permits, and sales history. Minor gaps like zoning or tax history are minor; the set is comprehensive for typical use cases.
Average 4.5/5 across 8 of 8 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under Apache 2.0.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
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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?
No annotations provided, so description carries full burden. It discloses that coverage varies by jurisdiction (top-100 metros complete, smaller may be empty) and lists returned fields. Does not explicitly state read-only, but implied. Good context for an agent.
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?
Five sentences, each adding unique value: purpose, field list, positive usage, negative usage, coverage caveat. Front-loaded with purpose. No fluff.
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?
Covers purpose, usage, field details, and coverage limitations. Lacks mention of pagination or default ordering, but given the tool's simplicity, it is fairly complete. No output schema, so description of return values is adequate.
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 100%, so baseline is 3. The description does not add extra meaning beyond the schema's parameter descriptions; it only mentions parcel_id implicitly. No additional value.
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?
Clearly states it returns a timeline of permits for a parcel, listing specific fields. Distinguishes from sibling 'parcel.search' by saying not to use for finding properties with permits across a market.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use (construction activity, renovations, planned work) and when not to use (finding properties with permits across a market, deferring to parcel.search). Also provides coverage caveat.
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?
Adds context beyond schema: backend index, query types, default/max limits, and summary fields. Lacks explicit read-only statement but no annotations to contradict.
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?
Four sentences with purpose first, then return structure, usage guidance, and backend context. No redundant 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?
Covers core use cases, filtering, pagination, and sibling differentiation. Lacks detail on error handling and exact ranking logic, but sufficient given no 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?
With 50% schema coverage, the description clarifies `q` usage and limit defaults but does not detail other parameters like `sort`, `dir`, or `page` beyond schema constraints.
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 'Filter US parcels by geography + attributes' and differentiates from siblings with explicit 'Do NOT use' instructions for parcel.lookup and parcel.compare.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides concrete use cases ('absentee-owned SFR in Mecklenburg County...') and explicit when-not-to-use scenarios, giving the agent clear decision criteria.
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 provided, so description carries full burden. It discloses coverage varies by hazard and geographic region, references the API endpoint, and implies read-only behavior. Lacking explicit statement that it does not modify data.
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?
Front-loaded with purpose, then usage, then coverage notes. Single paragraph is efficient but could be slightly more concise; still highly informative.
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 no output schema, description explains sub-scores and sources sufficiently for selection. Coverage details help set expectations. Lacks output structure but acceptable for this tool type.
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?
Schema covers 100% of parameters, but description adds value: explains parcel_id format (composite from parcel.lookup) and that include is a subset filter. Reinforces and clarifies beyond 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 it provides a composite hazard score for a parcel, listing specific hazards (flood, wildfire, seismic, etc.) with sources. It distinguishes from sibling tool parcel.compare for multiple parcels.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says when to use (property risk profile, insurance pricing) and when not to (comparing multiple parcels, suggesting parcel.compare). Also mentions coverage variations by region.
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?
Describes veil-piercing capability and data sources (SEC, sponsor rollup, county filings). Mentions return structure and confidence levels. No annotations provided, so description carries full burden. Could mention idempotence/side effects, but implied read-only.
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?
Well-structured with front-loaded purpose and actionable guidance. Each sentence adds value; slightly long but not excessive.
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?
Covers return structure, confidence tiers, and example use cases. No output schema, so description compensates well. Lacks error handling info but overall sufficient for the complexity.
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?
Adds context beyond schema: name normalization, state filter optional, ticker resolution logic. Schema descriptions are already good; tool description enriches understanding.
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?
Clearly states the tool resolves an owner name/entity to its full property portfolio. Distinguishes from sibling parcel.lookup by explicitly saying when not to use it.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says when to use (user names an owner) and when not to use (starting from a parcel, use parcel.lookup). Also describes ticker behavior and best-effort resolution.
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 provided, so description carries full burden. It discloses behavior for different query types: composite ID is direct lookup, address uses fuzzy search returning top 5, APN is fallback. However, it does not mention failure modes, rate limits, or authorization requirements.
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?
Two concise sentences plus examples. No filler. Purpose is front-loaded. 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?
Without an output schema, description explains return fields sufficiently. However, it omits edge cases (e.g., no match), error handling, or pagination for address search. Given the tool's simplicity, it is mostly 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?
Schema already describes the three forms of the 'query' parameter with 100% coverage. Description adds value by indicating preferred form (composite ID) and specifying that address uses fuzzy search and returns top 5 results, which goes beyond 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?
Description clearly states it resolves a single parcel by identifier, specifying accepted formats (composite ID, address, APN) and listing returned fields (identity, owner, valuation, geography, provenance). It distinguishes from siblings by mentioning when to use parcel.compare and parcel.search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use (user names one specific property) and when not to use (ranking multiple parcels → parcel.compare; filtering by criteria → parcel.search). Provides concrete examples of invocation.
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 discloses that the tool returns a current snapshot, notes that as_of is not supported, and gives accuracy context. Could mention rate limits or response structure, but overall provides good transparency.
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?
Three sentences, front-loaded with purpose and scope, no wasted words. Every sentence adds value: purpose, usage guidance, and behavioral caveat. Excellent conciseness.
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 no output schema, the description explains the return components (market estimate, assessed value, etc.). It covers limitations and unsupported features. Could mention typical response format or authentication requirements, but is largely complete for the tool's complexity.
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?
Schema coverage is 100%, so baseline is 3. The description adds value by explicitly noting that the as_of parameter is not yet supported and ignored, which is crucial for correct invocation. Parcel_id is already described in schema, but the additional context elevates the score.
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 estimated market value for a parcel, including specific components like assessed value and last sale price. It distinguishes from siblings by listing what it provides and implying it's the go-to for valuation queries, unlike other tools like sales.history.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use the tool (user asks for property value, market estimate, AVM, or comparing assessed vs market) and when not to use (substitute for an appraisal). Also provides accuracy limitations (MAE ±10-15%), guiding appropriate use.
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 provided, but the description clarifies that the agent is responsible for scoring and ranking, and that criteria are echoed back. It does not mention destructive actions, auth needs, or rate limits, but the behavioral scope is well-defined for a compare-only tool.
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 four sentences, each serving a distinct purpose: purpose, output and agent role, use case label, and usage boundaries. No redundant information.
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?
Given no output schema or annotations, the description adequately explains input format, output content (full reports per parcel), the agent's role in scoring, and the tool's place in the workflow (underwriting/shortlist loop).
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?
Schema coverage is 100%, and the description adds value beyond the schema by providing an example ID format ("37183:0012345"), specifying how to obtain IDs, and explaining that the criteria argument is echoed back for scoring.
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 explicitly states the verb 'Fetch reports for 2–25 parcels so they can be ranked against criteria' and distinguishes from sibling tools by noting alternatives for discovery (parcel.search) and single-property lookup (parcel.lookup + hazard.score).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Clearly states when to use: 'when the user has identified candidate properties' and includes explicit negative instructions: 'Do NOT use to discover new candidates (use parcel.search) or for a single property (use parcel.lookup + hazard.score).'
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 fully handles behavioral disclosure. It notes the side effect of include_liens=true making an extra API call and highlights that 13 states do not disclose sale prices. It does not explicitly state the tool is read-only, but the context implies it. No contradictions.
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?
Concise yet informative; the purpose is front-loaded, followed by usage guidelines, behavioral notes, and parameter clarification. Every sentence adds value with no redundancy.
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?
Despite no output schema, the description explains return event fields (date, price, buyer, seller, deed type) and flags for undisclosed prices. It also covers state-level limitations and side effects, making it complete for this tool's complexity.
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?
Schema coverage is 100%, so the description adds value beyond schema by clarifying that 'since' is a client-side filter and that 'include_liens' adds an extra API call with default false. This nuance aids 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 clearly states it provides a deed/transaction timeline for a parcel, listing specific event details (date, price, buyer, seller, deed type). This specific verb+resource distinguishes it from sibling tools like parcel.search or valuation.estimate.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use (user asks about transaction history, flip activity, holding period) and when not to use (market-wide sold properties or current value estimation), with direct references to alternative tools (parcel.search, valuation.estimate).
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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