Skip to main content
Glama

Leadconnector

Discover Tools

discover_tools
Read-onlyIdempotent

Find tools by describing the data or task. Use when you need to browse, search, look up, or discover what tools exist for: SEC filings, financials, revenue, profit, FDA drugs, adverse events, FRED economic data, Census demographics, BLS jobs/unemployment/inflation, ATTOM real estate, ClinicalTrials, USPTO patents, weather, news, crypto, stocks. Returns the top-N most relevant tools with names, descriptions, and full input schemas (with curated examples) — each result is ready to call directly, no second schema lookup needed. Call this FIRST when you have many tools available and want to see the option set (not just one answer).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoAlias for query.
taskNoAlias for query.
limitNoMaximum number of tools to return (default 20, max 50)
queryYesNatural language description of what you want to do (e.g., "analyze housing market trends", "look up FDA drug approvals", "find trade data between countries"). Accepts task, q, description, search as aliases.
searchNoAlias for query.
descriptionNoAlias for query.

TDQS

A4.5/5.0
Behavior4/5

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

Annotations indicate readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds valuable behavior: returns schemas with curated examples, results ready to call directly, and covers a wide range of data sources. No contradictions with annotations. A 4 is appropriate as it provides useful context beyond 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?

The description is concise yet comprehensive: first sentence states purpose, second lists domains, third explains return value, fourth gives usage guideline. Every sentence adds value, and the most important info is front-loaded. No wasted words.

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 the tool's complexity (meta-discovery across many domains), the description covers purpose, usage, return format, and domain scope. No output schema is needed because the description already explains the return. All relevant aspects are addressed for a discovery tool.

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 all parameters have descriptions. The description explains the query parameter as 'natural language description' and mentions acceptable aliases, which adds marginal value. The examples in the schema provide concrete usage. Baseline 3 raised to 4 due to the examples and alias clarification.

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 'Find tools by describing the data or task.' It specifies many domains (SEC filings, FDA, etc.) and explains that it returns top-N relevant tools with full schemas. This distinctly differentiates it from sibling tools, which are domain-specific.

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 explicitly says 'Call this FIRST when you have many tools available and want to see the option set (not just one answer).' This provides clear context for when to use. However, it does not explicitly state when not to use or mention alternatives, though the sibling list implies this is the discovery entry point.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.5/5.0
Disambiguation2/5

Multiple tools have overlapping purposes, such as ask_pipeworx and ask_pipeworx_grounded, or bet_research and polymarket_edges. The mix of CRM, data, and betting tools creates confusion about which tool to use for a given task.

Naming Consistency2/5

Tool names are inconsistent, mixing snake_case (ai_visibility_check, ask_pipeworx) with prefixed names (leadconnector_*) and no clear pattern. Some names are vague (forget, remember) while others are specific.

Tool Count2/5

With 32 tools, the set feels overstuffed for a server named 'Leadconnector'. Many tools are unrelated to CRM (e.g., Polymarket, Pipeworx), and the CRM subset is too small to justify the count.

Completeness2/5

For the Leadconnector CRM domain, only basic read operations are provided; missing create, update, delete for contacts, campaigns, and opportunities. The non-CRM tools are comprehensive but don't match the server's name.