Skip to main content
Glama

Data Cambridge

by io.github.pipeworx-io

Cambridge Datasets

cambridge_datasets
Read-onlyIdempotent

Search the Cambridge open-data catalogue (data.cambridgema.gov) for datasets by keyword. Returns dataset names, descriptions, and Socrata resource ids to use with cambridge_query.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax datasets (1-100, default 20).
queryNoKeyword(s), e.g. "parking", "housing", "tree".
offsetNoOffset for paging.
_apiKeyNoOptional — your own Socrata app token for higher rate limits. Omit to use the keyless endpoint.

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive. The description adds value by specifying the data source (data.cambridgema.gov) and the return contents, 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 concise sentences, front-loaded with action and source. Every word contributes, no fluff.

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?

No output schema is present, but the description adequately summarizes return fields (names, descriptions, resource IDs) and links to the related tool. Given the tool's simplicity and full annotation coverage, it is complete.

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 100% schema description coverage, the schema already explains parameters. The description adds context about the 'query' parameter (keyword search) and return usage, but doesn't significantly deepen parameter 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?

The description clearly states the action (search) and the resource (Cambridge open-data catalogue), specifies output (dataset names, descriptions, Socrata resource ids), and distinguishes from sibling tools like cambridge_query by indicating the output is meant for use with that tool.

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 indicates when to use (searching by keyword) and how the result feeds into cambridge_query, but lacks explicit exclusions or alternative tool recommendations. Context from sibling names helps but isn't explicit in the description.

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

All Data Cambridge toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.9/5.0
Disambiguation3/5

Most clusters have clear roles, and the detailed routing guidance separates ask_pipeworx from deep_research and grounded mode. However, three ask_pipeworx variants (one currently identical to stable), plus overlapping opportunity-discovery tools (polymarket_edges vs bet_research) and discovery/onboarding tools (discover_tools vs suggest_questions), leave several boundary cases where an agent could select the wrong tool.

Naming Consistency3/5

Many tools group under readable prefixes (ask_pipeworx, cambridge_, polymarket_, pipeworx_) and are mostly snake_case. But the set mixes bare verbs (remember, recall, forget), verb_noun actions (resolve_entity, validate_claim), and noun-phrase names (entity_profile, recent_changes, polymarket_fill_risk), so no single convention predicts the full API.

Tool Count2/5

34 tools is well into the 'too many' band, and the count is inflated by a kitchen-sink mix of data querying, prediction-market analysis, memory, subscriptions, feedback, llms.txt generation, and npm scanning. The server name 'Data Cambridge' suggests a narrow local-data scope, which makes the sprawl look even less appropriate.

Completeness3/5

Individual verticals are fairly complete: query/grounded/beta router levels, entity resolution/profile/compare/change, prediction-market discovery through fill-risk, and full memory and subscription CRUD. The major gap is discover_tools, which returns tools promoted as ready to call directly but no generic invocation tool is exposed, so the agent must route back through ask_pipeworx.

Resources