FrankSpace Public MCP
Server Details
Read-only search over live UK office & workspace listings on FrankSpace.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Tool access control
Enable or disable individual tools per connector, so you decide what your agents can and cannot do.
Managed credentials
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Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
Tool Definition Quality
Average 4.2/5 across 3 of 3 tools scored.
Each tool has a distinct purpose: ai_search handles natural-language queries, search_workspaces handles structured filters, and get_workspace retrieves details by ID. No overlap.
All tools use lowercase with underscores (ai_search, get_workspace, search_workspaces). The verb pattern is mostly consistent (get, search), though 'ai_search' starts with a noun rather than a verb.
Three tools is appropriate for a public read-only workspace listing service: two search methods (natural-language and structured) plus a detail fetcher. No extraneous tools.
The set covers the core read operations: searching (two modes) and fetching details. As a public API, CRUD isn't expected. A minor gap is the lack of a pure 'list all' endpoint, but search covers it.
Available Tools
3 toolsai_searchNatural-language workspace searchARead-onlyIdempotentInspect
Search FrankSpace workspaces with a plain-English query — the same AI parser that powers the app. Handles budgets, headcount, neighbourhoods, amenities, EPC ratings, and lease terms. Returns matching live UK listings.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Plain-English search query, e.g. 'small office for 6 people in Shoreditch under £3k'. | |
| client_hint | No | Name of the calling agent (e.g. 'claude', 'chatgpt', 'cursor') for analytics. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and openWorldHint. Description adds that it uses the app's AI parser and returns live UK listings, providing useful context beyond annotations without contradiction.
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, front-loaded with purpose, no wasted words. Every sentence adds essential 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?
Given the tool's complexity (NL search) and good schema/annotation coverage, the description is mostly complete. It explains return content (live UK listings) but omits details like pagination or result limits, which are minor for this context.
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 covers both parameters with descriptions. The description adds value by giving example queries and listing queryable aspects, enriching understanding beyond the schema alone.
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 it searches FrankSpace workspaces with plain-English queries, listing specific capabilities (budgets, headcount, etc.). Distinguishes from siblings like get_workspace (by ID) and search_workspaces (structured) by emphasizing natural language.
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?
Implies usage for natural-language queries vs structured search in siblings, but does not explicitly state when to use alternatives or provide exclusions. Context is clear but lacks explicit when-not guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_workspaceGet workspace detailsARead-onlyIdempotentInspect
Fetch full public details for a single FrankSpace workspace by its ID (UUID).
| Name | Required | Description | Default |
|---|---|---|---|
| client_hint | No | Name of the calling agent (e.g. 'claude', 'chatgpt') for analytics. | |
| workspace_id | Yes | Workspace UUID. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true, openWorldHint=false, idempotentHint=true. The description adds that it fetches 'public details', confirming no side effects. This adds some context beyond annotations but not extensively.
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, clear and front-loaded. No extraneous words; every part is necessary. Efficient and to the point.
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 fetch tool with 2 parameters, 100% schema coverage, and annotations, the description is sufficient. It explains the purpose and key parameter. No output schema, but 'full public details' hints at the return structure.
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%: both 'client_hint' and 'workspace_id' have descriptions. The description reinforces 'workspace_id' as UUID, but adds no new information beyond the schema. Baseline 3 is appropriate.
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 verb 'Fetch', the resource 'full public details for a single FrankSpace workspace', and the method 'by its ID (UUID)'. It distinguishes from sibling tools like 'search_workspaces' which likely lists multiple workspaces, and 'ai_search' for AI-related searches.
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 needing full details for a single workspace by ID. It does not explicitly state when not to use it or mention alternatives like 'search_workspaces', but the context is clear enough for the agent to infer.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_workspacesSearch FrankSpace workspacesARead-onlyIdempotentInspect
Search live UK workspace listings on FrankSpace. Filter by location text (city, postcode, submarket), size band, and maximum monthly price (pence). For richer natural-language queries prefer ai_search.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| location | No | Free-text location, e.g. 'Shoreditch' or 'EC2A'. | |
| size_band | No | small ≤500 sqft, medium 500-1500, large 1500-3000, xlarge >3000. | |
| client_hint | No | Name of the calling agent (e.g. 'claude', 'chatgpt') for analytics. | |
| max_price_pence | No | Max monthly price in pence. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and idempotentHint. The description adds that listings are 'live UK' and provides filter specifics, which are beyond the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences: first defines purpose, second lists filters and alternative. No wasted words, front-loaded with core action.
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 the lack of output schema and 5 parameters, the description covers domain, filters, and usage boundaries. It omits pagination details but the default limit and min/max are in schema.
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 80%, and the description largely restates what the schema already explains. It does not add new meaning beyond grouping filters into a summary.
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 live UK workspace listings on FrankSpace, listing specific filters. It explicitly distinguishes from the sibling 'ai_search' for natural-language queries.
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 explicitly advises against using this tool for rich natural-language queries, directing to 'ai_search'. It does not mention 'get_workspace', but the context implies it for individual workspace lookups.
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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{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
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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
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