Skip to main content
Glama

FrankSpace Public MCP

Server Details

Read-only search over live UK office & workspace listings on FrankSpace.

Status
Healthy
Last Tested
Transport
Streamable HTTP
URL

Glama MCP Gateway

Connect through Glama MCP Gateway for full control over tool access and complete visibility into every call.

MCP client
Glama
MCP server

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.

100% free. Your data is private.
Tool DescriptionsA

Average 4.3/5 across 3 of 3 tools scored.

Server CoherenceA
Disambiguation4/5

The three tools have mostly distinct purposes: ai_search handles natural-language queries, search_workspaces handles structured filters, and get_workspace retrieves details by ID. There is some overlap between the two search tools, but descriptions clarify when to use each, minimizing ambiguity.

Naming Consistency3/5

Two tools follow the verb_noun pattern (get_workspace, search_workspaces), but ai_search uses a prefix style that breaks the pattern. This inconsistency, while not chaotic, reduces predictability.

Tool Count4/5

With only 3 tools, the server feels minimal but focused. The count is appropriate for a simple lookup and search API, though a few more tools (e.g., list amenities or nearby locations) would be expected for a full-featured workspace database.

Completeness4/5

The tool set covers the core operations: searching (both natural-language and structured) and retrieving details. However, it lacks listing all workspaces or advanced filtering (e.g., by amenities), which are minor gaps in an otherwise complete surface for basic querying.

Available Tools

5 tools
get_frankspace_skillHow to use FrankSpaceA
Read-onlyIdempotent
Inspect

Fetch the FrankSpace Agent Skill: how to query the listing inventory correctly, how to read the data (prices are pence, IDs are UUIDs), the commercial facts, and the limits of what this server can do. Read this once before your first search if you are unfamiliar with FrankSpace.

ParametersJSON Schema
NameRequiredDescriptionDefault
client_hintNoName of the calling agent (e.g. 'claude', 'chatgpt') for analytics.
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already mark it as read-only, idempotent, and closed-world. The description adds valuable context about the content of the skill (e.g., data format, limitations), which helps the agent understand what to expect without contradicting annotations.

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 sentences that front-load the action ('Fetch the FrankSpace Agent Skill') and succinctly cover the document's content and recommended usage. 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?

The tool is simple (one optional param, no output schema). The description explains the skill's content sufficiently for an agent to understand when and why to call it. Minor omission: no mention of the parameter's effect, but the tool works without it.

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 has 100% description coverage for the single optional parameter 'client_hint,' so baseline is 3. The description does not elaborate on this parameter, but it is not necessary for understanding the tool's core purpose.

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 it fetches the 'FrankSpace Agent Skill' document, which instructs on querying inventory, reading data (prices as pence, IDs as UUIDs), and understanding server limits. This clearly differentiates it from sibling tools like 'ai_search' or 'get_workspace.'

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 advises reading the skill 'once before your first search if you are unfamiliar with FrankSpace,' providing a clear use case. It does not explicitly state when not to use it or mention alternatives, but the context is sufficiently clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

get_workspaceGet workspace detailsA
Read-onlyIdempotent
Inspect

Fetch full public details for a single FrankSpace workspace by its ID (UUID).

ParametersJSON Schema
NameRequiredDescriptionDefault
client_hintNoName of the calling agent (e.g. 'claude', 'chatgpt') for analytics.
workspace_idYesWorkspace UUID.
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already provide readOnlyHint, idempotentHint, and openWorldHint. The description adds that details are 'public', which is helpful but minimal. It does not contradict annotations, but adds little beyond them.

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, well-structured sentence that immediately conveys the core purpose. No unnecessary words or 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?

For a simple read tool with strong annotations and a self-explanatory schema, the description sufficiently explains what the tool does and what it returns ('full public details'). No output schema is needed.

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 input schema has 100% description coverage for both parameters. The description does not add any additional meaning beyond the schema's own parameter 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 ('Fetch'), a clearly defined resource ('full public details for a single FrankSpace workspace'), and a precise method ('by its ID (UUID)'). This effectively distinguishes it from sibling search tools like 'search_workspaces'.

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 implicitly indicates usage (fetching a single workspace by ID), but lacks explicit guidance on when to use this tool versus alternatives like 'search_workspaces' or 'ai_search'. No 'when not to use' or direct comparison is provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

search_workspacesSearch FrankSpace workspacesA
Read-onlyIdempotent
Inspect

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.

ParametersJSON Schema
NameRequiredDescriptionDefault
limitNo
locationNoFree-text location, e.g. 'Shoreditch' or 'EC2A'.
size_bandNosmall ≤500 sqft, medium 500-1500, large 1500-3000, xlarge >3000.
client_hintNoName of the calling agent (e.g. 'claude', 'chatgpt') for analytics.
max_price_penceNoMax monthly price in pence.
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint and idempotentHint. The description adds context about the domain (live UK workspace listings) and filtering capabilities, but does not detail return format or pagination behavior, which is acceptable given annotations.

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 sentences with no fluff. Purpose is front-loaded, and the alternative tool reference is efficiently placed. Every sentence earns its place.

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?

The description covers the main filtering options and domain. However, it omits mention of the 'limit' parameter (pagination) and the 'client_hint' parameter, leaving minor gaps. For a search tool without output schema, this is acceptable but not fully 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 description coverage is 80%, so baseline is 3. The description adds value by specifying that location can be city, postcode, or submarket, and mentions size band and max price. This clarifies the intended use beyond the schema's individual parameter 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 clearly states the verb 'Search' and the resource 'live UK workspace listings on FrankSpace'. It distinguishes from sibling 'ai_search' by specifying structured filter capabilities and explicitly directing richer queries to 'ai_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 instructs when to use this tool: for filtering by location, size band, and max price. Provides an alternative ('ai_search') for natural-language queries, making the choice clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

submit_feedbackReport a problem with FrankSpace data or docsAInspect

Report something wrong or missing in FrankSpace's agent-facing surface: a listing whose details look stale or incorrect, a gap that made a search impossible, an unclear or contradictory statement in llms.txt / skill.md, or a tool that behaved unexpectedly. Feedback is reviewed by the FrankSpace team. Do NOT use this to contact a property owner, register interest in a workspace, ask a question, or pass on anything a user expects a reply to — nobody replies to this channel. Enquiries and viewings go through the listing page at https://frankspace.co.uk/office/, by the user, on the site. Send one clear report rather than several; describe what you observed and what you expected.

ParametersJSON Schema
NameRequiredDescriptionDefault
kindNodata_error: a listing's details are wrong or stale. missing_data: a field or filter you needed does not exist. docs_unclear: llms.txt / skill.md is unclear, contradictory or incomplete. tool_problem: a tool errored or returned something unusable.other
messageYesWhat is wrong, in plain English. Include what you observed and what you expected. Do not include personal data about the user.
client_hintNoName of the calling agent (e.g. 'claude', 'chatgpt') for analytics.
subject_urlNoThe FrankSpace URL the report is about, if not a specific workspace.
workspace_idNoUUID of the workspace the report is about, when it concerns one listing.
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description adds behavioral context beyond annotations: feedback is reviewed by the team, nobody replies to this channel, and it specifies what kind of feedback is appropriate. Annotations are neutral (no readOnly, no destructive hints), and the description does not contradict them.

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 well-structured with clear examples and exclusions. It is front-loaded with purpose and then details. Though slightly long, 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 the complexity (5 parameters, 1 required) and no output schema, the description provides sufficient context for agents to understand the tool's purpose and how to report issues. It covers the types of problems and what to include.

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 the schema already documents all five parameters thoroughly. The tool description does not add additional parameter-level detail beyond the schema. Baseline of 3 is appropriate.

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 ('Report') and explicitly lists the types of problems (data errors, missing data, docs unclear, tool problems) that fall under this tool. It clearly distinguishes from sibling tools like ai_search, get_workspace, etc., which serve different purposes.

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?

The description provides explicit when-to-use ('Report something wrong or missing') and when-not-to-use ('Do NOT use this to contact a property owner...', 'Enquiries and viewings go through the listing page'). It also gives guidance on sending one clear report rather than several.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Discussions

No comments yet. Be the first to start the discussion!

Related MCP Servers

  • A
    license
    A
    quality
    C
    maintenance
    Unified UK property search across major portals with deduplication and open-data enrichment, enabling natural-language queries for listings, sold prices, EPC, crime, schools, and market stats.
    10
    MIT
  • A
    license
    A
    quality
    D
    maintenance
    Enables users to search UK property prices by postcode, street, or city using the HM Land Registry's SPARQL endpoint. It also provides tools for resolving postcodes and finding nearby locations through Ordnance Survey data.
    2
    2
    MIT
  • F
    license
    -
    quality
    C
    maintenance
    Turns open places data into AI-assisted local market intelligence, enabling search of 4.4 million UK places by category, location, and proximity, and saving promising results to a prospecting pipeline.

View all MCP Servers

Try in Browser

Your Connectors

Sign in to create a connector for this server.

Resources