Commercial real estate intelligence for investors, brokers, and developers across 9 Northeast US states (CT, MA, NJ, NY, PA, RI, NH, VT, ME).
Every commercial listing is scored 1–10 using a 5-dimension framework: income yield, value-add potential, basis/location, exit/1031 suitability, and deal structure. Pull scored deals, comp-backed benchmarks, 1031 exchange candidates, and sell signals — all backed by 20,000+ active listings and 109,000+ closed sale comps.
**sear
Glama MCP Gateway
Connect through Glama MCP Gateway for full control over tool access and complete visibility into every call.
Full call logging
Every tool call is logged with complete inputs and outputs, so you can debug issues and audit what your agents are doing.
Tool access control
Enable or disable individual tools per connector, so you decide what your agents can and cannot do.
Managed credentials
Glama handles OAuth flows, token storage, and automatic rotation, so credentials never expire on your clients.
Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
Average 2.9/5 across 5 of 5 tools scored.
Each tool targets a distinct aspect of commercial real estate: finding 1031 exchange candidates, market benchmarks, market summaries, deal scoring, and deal searching. No overlap in purpose.
All tool names follow a clear verb_noun pattern (find, get, score, search) with consistent snake_case, making them predictable and easy to understand.
Five tools is an ideal size for this domain, covering key workflows without being overwhelming or sparse. Each tool serves a well-defined function.
The tool surface covers the core needs of a real estate deal intelligence platform: finding replacement properties, obtaining market data, scoring deals, and searching listings. No obvious gaps for the stated purpose.
find_1031_candidatesCInspectFind NNN and near-NNN replacement properties suitable for 1031 exchange buyers.
| Name | Required | Description | Default |
|---|---|---|---|
| state | No | CT | |
| max_price | No | ||
| min_price | No | ||
| min_cap_rate | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description only states purpose without disclosing behavioral traits such as read-only nature, return format, or action side effects.
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?
Single sentence is concise and front-loads the purpose, but lacks structure to cover additional needed information.
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?
With 4 parameters, no output schema, and no annotations, the description is far too minimal to provide adequate context for correct tool invocation.
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% and the description does not explain any of the 4 parameters (state, max_price, min_price, min_cap_rate), leaving the agent without guidance.
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?
Description clearly states the tool finds NNN and near-NNN replacement properties for 1031 exchange buyers, distinguishing it from sibling tools like get_market_benchmarks or search_deals.
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?
Implied usage for 1031 exchange buyers, but no explicit guidance on when to use vs alternatives or when not to use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_market_benchmarksBInspectGet live cap rate and price/SF benchmarks by state and property type, backed by 109,000+ comps.
| Name | Required | Description | Default |
|---|---|---|---|
| state | No | CT | |
| property_type | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of disclosing behavioral traits. It states the data is 'live' and from a large comp set, but fails to mention whether the tool is read-only, idempotent, or if there are rate limits, authentication requirements, or side effects. The agent lacks critical safety information.
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 a single sentence of 18 words, efficiently conveying the tool's purpose and a key fact (data size). Every element is meaningful, and the most important information is 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?
For a simple tool with no output schema, the description provides the essential purpose and filter criteria. However, it does not indicate the return structure (e.g., single benchmark vs. list) or clarify behavior when property_type is empty. Given the low parameter count and lack of annotations, slightly more context would improve completeness.
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 input schema has 0% description coverage, so the description must compensate. It mentions filtering by state and property type, but does not clarify allowed values, default meanings, or formatting (e.g., 'CT' as two-letter code). The default values ('CT' and empty string) are not explained, leaving ambiguity about behavior.
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's purpose: to retrieve live cap rate and price/SF benchmarks, filtered by state and property type. The mention of '109,000+ comps' adds credibility and specificity. It distinguishes itself from siblings like get_market_summary by focusing on benchmarks rather than summary statistics.
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 provided on when to use this tool versus alternatives such as get_market_summary or search_deals. The description does not mention prerequisites, exclusions, or context for when this tool is appropriate over others.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_market_summaryCInspectGet a market summary for a state: active listings, avg cap rate, top submarkets, recent velocity.
| Name | Required | Description | Default |
|---|---|---|---|
| state | No | CT |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It does not mention that this is a read-only operation, any side effects, data freshness, or permissions required. The agent cannot infer safety or cost implications.
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?
Single sentence that front-loads the action and lists key contents. Efficient, though could be slightly more structured with bullet points or explicit parameter mention.
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 simple tool with one parameter and no output schema, the description covers the core purpose and output components. However, it lacks detail on output format, response structure, and parameter constraints, leaving some ambiguity.
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 coverage is 0%, but the description does not add meaning to the state parameter beyond what the schema shows. It omits format (e.g., two-letter code), allowed values, or behavior when omitted. The default 'CT' is noted in schema but not explained.
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 it gets a market summary for a state and lists included data points (active listings, avg cap rate, top submarkets, recent velocity). This is specific and distinguishes from sibling tools like get_market_benchmarks, though not explicitly differentiated.
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 on when to use this tool versus alternatives. For example, it could contrast with get_market_benchmarks or indicate use cases like 'for high-level overview'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
score_dealBInspectScore a commercial real estate deal 1-10 using NDI's 5-dimension framework.
| Name | Required | Description | Default |
|---|---|---|---|
| state | Yes | ||
| address | Yes | ||
| cap_rate | No | ||
| asking_price | Yes | ||
| property_type | Yes | ||
| days_on_market | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must fully convey behavioral traits. It only states the scoring output (1-10) and framework, but does not disclose what happens with invalid inputs, whether the deal must exist, or any side effects. Limited insight into tool behavior.
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?
Single sentence is efficient but may be too terse. It captures core purpose but misses opportunity to add valuable context without bloating. Adequate but not optimally informative.
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?
With 6 parameters, no output schema, and no parameter descriptions, the description is incomplete. It does not explain the NDI framework, the output format, or how parameters influence scoring. Users lack context to use the tool effectively.
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% (no property descriptions). The tool description does not explain any parameters beyond the overall purpose. Users must infer that address, state, property type, asking price, etc., are required inputs, but no guidance on their role or format.
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?
Description clearly states the tool scores a commercial real estate deal using a specific framework (NDI's 5-dimension) and outputs a 1-10 rating. Distinguishes from siblings like search_deals (which finds deals) and get_market_benchmarks (which provides benchmarks).
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?
Description implies when to use: when a deal scoring is needed. However, it does not explicitly state when not to use or compare with alternatives. Sibling tools are listed but no guidance on selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_dealsCInspectSearch scored commercial real estate listings. Returns deals scored 1-10 with cap rates, flags, and analyst takes.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| state | No | CT | |
| max_price | No | ||
| min_score | No | ||
| min_cap_rate | No | ||
| property_type | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavioral traits. It does not mention authentication needs, rate limits, destructive potential, or whether it supports write operations. The description implies read-only search but does not confirm.
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 (two sentences) but not front-loaded with the most critical information. It lacks structure and does not prioritize key details. While concise, it sacrifices clarity for brevity.
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 6 parameters, no output schema, and no annotations, the description is severely incomplete. It fails to document parameter usage, output structure, or edge cases. The return fields mentioned (cap rates, flags, analyst takes) are insufficient for an agent to fully understand the tool's capabilities.
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% and the description does not explain any of the 6 parameters. The schema provides only names, types, and defaults. The description adds no meaning beyond the schema about parameters like state, max_price, min_score, etc.
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 searches for scored commercial real estate listings and returns scores, cap rates, flags, and analyst takes. It provides a specific verb and resource, though it does not explicitly differentiate from sibling tools like find_1031_candidates or score_deal.
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 on when to use this tool versus alternatives. The description lacks context about prerequisites, when it is appropriate, or 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.
Claim this connector by publishing a /.well-known/glama.json file on your server's domain with the following structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
}The email address must match the email associated with your Glama account. Once published, Glama will automatically detect and verify the file within a few minutes.
Control your server's listing on Glama, including description and metadata
Access analytics and receive server usage reports
Get monitoring and health status updates for your server
Feature your server to boost visibility and reach more users
For users:
Full audit trail – every tool call is logged with inputs and outputs for compliance and debugging
Granular tool control – enable or disable individual tools per connector to limit what your AI agents can do
Centralized credential management – store and rotate API keys and OAuth tokens in one place
Change alerts – get notified when a connector changes its schema, adds or removes tools, or updates tool definitions, so nothing breaks silently
For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
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
The connector status is unhealthy when Glama is unable to successfully connect to the server. This can happen for several reasons:
The server is experiencing an outage
The URL of the server is wrong
Credentials required to access the server are missing or invalid
If you are the owner of this MCP connector and would like to make modifications to the listing, including providing test credentials for accessing the server, please contact support@glama.ai.
No comments yet. Be the first to start the discussion!
