Skip to main content
Glama

Startup Oracle

by io.github.pipeworx-io

Remember

remember
Idempotent

Save data the agent will need to reuse later — across this conversation or across sessions. Use when you discover something worth carrying forward (a resolved ticker, a target address, a user preference, a research subject) so you don't have to look it up again. Stored as a key-value pair scoped by your identifier. Authenticated users get persistent memory; anonymous sessions retain memory for 24 hours. Pair with recall to retrieve later, forget to delete.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyYesMemory key (e.g., "subject_property", "target_ticker", "user_preference")
valueYesValue to store (any text — findings, addresses, preferences, notes)

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.7/5.0
Behavior5/5

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

Beyond annotations (idempotent, non-destructive), description adds scope (key-value pair by identifier) and persistence details (24h for anonymous, persistent for authenticated). No contradiction.

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?

Four sentences, front-loaded with purpose, no fluff. Well-structured and easy to parse.

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 simple 2-param tool with annotations, description fully covers purpose, usage, behavior, and complementary tools. No gaps.

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 covers 100% with descriptions for both key and value. Description adds minor context (key examples, value is any text) but doesn't significantly enhance 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?

Clearly states verb 'save' and resource 'data', distinguishing from siblings 'recall' and 'forget'. Examples clarify what data to store.

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 says when to use ('discover something worth carrying forward') and provides examples. Also mentions complementary tools for retrieval and deletion.

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

All Startup Oracle 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

A3.6/5.0
Disambiguation2/5

ask_pipeworx_beta is explicitly identical to ask_pipeworx today, and ask_pipeworx_grounded is another variant of the same router, so an agent can easily misselect. Additionally, bet_research, polymarket_edges, and polymarket_arbitrage all present as prediction-market opportunity finders with overlapping responsibilities.

Naming Consistency3/5

Most tools follow snake_case verb_noun (ask_pipeworx, list_subscriptions, resolve_entity, unsubscribe, validate_claim), but several break the pattern with noun phrases like polymarket_edges and pipeworx_trending, plus oddities like startup_oracle_evaluate. The mix is readable but not predictable.

Tool Count2/5

32 tools is well over the 25 threshold and the set is not tightly scoped: prediction markets alone account for six overlapping tools, and the server also bundles memory, subscriptions, npm dependency scanning, llms.txt generation, and AI visibility checks. ask_pipeworx_beta adds a duplicate that does not earn its slot.

Completeness3/5

As a read-heavy research gateway, the surface is broad: lookups, profiles, comparisons, verification, deep research, discovery, and citation handling are covered, and the subscription/memory helpers have their own lifecycle operations. But the 'Startup Oracle' mission is thin — startup-specific evaluation is a single joke tool, and there is no way to update subscriptions or act on research findings beyond saving memory.

Resources