Skip to main content
Glama
Iqbalahmed7

Simulatte MCP Server

by Iqbalahmed7

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
SIMULATTE_API_KEYYesYour Simulatte API key starting with sim_live_

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Features and capabilities supported by this server

Protocol revision2025-11-25

CapabilityDetails
tools
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
simulatte_run_studyB

Run a Simulatte synthetic research study. Choose from 26 SKUs covering concept testing, pricing, messaging, B2B committee simulation, depth interviews, and more. Returns a study_id you can poll with simulatte_get_results.

simulatte_get_resultsA

Retrieve results for a completed Simulatte study. Returns full structured results JSON including verdicts, key drivers, objections, persona breakdowns, and Forge Loop recommendations.

simulatte_ask_insightsA

Ask a question across your entire Simulatte research history using semantic search. Returns a cited answer with themes and source study references. Great for synthesizing findings across multiple studies.

simulatte_list_poolsA

List all persona pools in your Simulatte workspace. Returns pool IDs, names, markets, and sizes. Use pool IDs in simulatte_run_study to target a specific audience segment.

simulatte_create_poolA

Create a new synthetic persona pool with a custom demographic and psychographic specification. Returns a pool_id you can reuse across multiple studies.

simulatte_depth_interviewA

Run a simulated depth interview with a synthetic persona. The persona responds in character across multiple turns, surfacing motivations, objections, and language naturally. Returns interview_id and a credits estimate.

simulatte_estimate_costA

Estimate the credit cost and USD price for a Simulatte study before running it. Calculated locally — no API call needed. Credits = base_cost_per_persona × sample_size.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

TDQS

A4/5.0

Scored across 7 tools

Disambiguation5/5

Every tool has a clearly distinct purpose, covering different stages of the research workflow: setting up pools, running studies/interviews, getting results and insights, and estimating costs. No two tools have overlapping functionality.

Naming Consistency5/5

All tools consistently use the 'simulatte_' prefix followed by a verb_noun pattern (e.g., create_pool, get_results), making names predictable and easy to understand.

Tool Count5/5

With 7 tools, the set is well-scoped for the server's purpose of synthetic research. Each tool addresses a necessary step without being excessive or insufficient.

Completeness4/5

The tools cover the core lifecycle—create pools, run studies, get results, ask insights, estimate costs. A minor gap is the lack of deletion or cancellation tools, but the essential workflows are complete.

Maintenance

ActivitySlowing
ResponsivenessNo issues