Everyrow MCP Server

by futuresearch·io.github.futuresearch/everyrow-mcp·v0.5.1·57 stars

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Give your AI a research team. Forecast, score, classify, or research every row of a dataset.

A85/100grade A

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Safety scan

A85/100

full report

Adoption

Growing

57 stars75 downloads/wk

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Everyrow MCP Server tools (16, 6 write)

write = sends, deletes, buys or posts

Read from the package source without running it. The installed server may list more.

everyrow_agentwrite action
Run web research agents on each row of a CSV file.
everyrow_balance
Check the current billing balance for the authenticated user.
everyrow_browse_lists
Browse available reference lists of well-known entities.
everyrow_cancelwrite action
Cancel a running everyrow task. Use when the user wants to stop a task that is currently processing.
everyrow_classify
Classify each row of a dataset into one of the provided categories.
everyrow_dedupewrite action
Remove duplicate rows from a CSV file using semantic equivalence.
everyrow_forecast
Forecast the probability of binary questions from a CSV file.
everyrow_list_session_tasks
List all tasks in a session with their IDs, statuses, and types.
everyrow_list_sessions
List everyrow sessions owned by the authenticated user (paginated).
everyrow_merge
Join two CSV files using intelligent entity matching.
everyrow_progress
Check progress of a running task. Blocks briefly to limit the polling rate.
everyrow_rank
Score and sort rows in a CSV file based on any criteria.
everyrow_request_upload_urlwrite action
Request a presigned URL to upload a local CSV file.
everyrow_single_agentwrite action
Run a single web research agent on a task, optionally with context data.
everyrow_upload_datawrite action
Upload data from a URL or local file. Returns an artifact_id for use in processing tools.
everyrow_use_list
Import a reference list into your session and make it available via artifact_id for other everyrow tools.

Public scan report

scanner v0.1.10 · 2026-09-27 · same rubric, same numbers if you re-run it

no findings

Code scan35 source files scanned25/25
–Live reliabilityno gateway calls yet and no remote to proben/a
–Tool poisoningtools not inspected (local package is not executed); not countedn/a
Auth qualitystatic API keys via environment variables6/15
Maintenancelast push 2 days ago15/15
Maintainer identityregistry namespace matches repository owner; GitHub account older than a year9/10

Overall 85/100. Components that don't apply are left out of the denominator. Any critical finding is an F.Rubric Appeal a finding JSON

How Everyrow MCP Server compares

Against every graded MCP server, from our own scans and uptime checks. Updated after each scan run.

Safety score: 85/100; higher than 70% of 48,255 servers
Tools: 16; the typical server has 7
Tools that change things: 38%; typical: 0%. Fewer write tools means less an agent can break
GitHub stars: 57; more than 95% of 28,688 servers
Downloads a week: 75; more than 56% of 12,191 servers with a package

What its tools let an agent do: 10 read · 6 change

Install Everyrow MCP Server in Claude Code, Cursor or VS Code

claude mcp add everyrow-mcp -- uvx everyrow-mcp

Add to Cursor

What the publisher says

From the Everyrow MCP Server repository's README, as published. We do not edit it. Read it on GitHub

FutureSearch Python SDK

An API for frontier forecasting.

FutureSearch predicts the future. Accuracy is verifiable via our public track record on stocks, prediction markets, public benchmarks, and forecasting tournaments: the forecaster leads Metaculus's Summer 2026 FutureEval tournament, sits above the superforecaster median on ForecastBench, and holds the best pooled score on BTF-3, our 1,907-question pastcasting benchmark. Those are live standings, so the link carries the current positions. Every forecast draws on a shared world model that reconciles related questions against each other; it improved all nine base forecasters we tested, four of them significantly.

Try it yourself in the app, or give advanced forecasting and multi-agent capabilities to your AI wherever you use it (Claude.ai, Claude Code, or Gemini/Codex/other AI surfaces), or point them to this Python SDK.

Installation

Claude.ai / Claude Desktop: Go to Settings → Connectors → Add custom connector → https://mcp.futuresearch.ai/mcp

Claude Code:

claude mcp add futuresearch --scope project --transport http https://mcp.futuresearch.ai/mcp

Then sign in the same way you do in the FutureSearch web app and pick the account the connection should use.

Forecasting

forecast() takes a table of questions about the future and returns a forecast for each row, with a rationale column explaining each answer. Five modes cover the shapes a question can take.

Effort level is "LOW" or "HIGH": roughly $0.15 per question at low effort and $2 at high effort. Left unset, a single question runs at high effort and a batch runs at low. Categorical, thresholded, and conditional forecasts always require "HIGH".

Binary

The probability, 0 to 100, that a YES/NO question resolves YES. Output columns: probability and rationale.

import asyncio
from pandas import DataFrame
from futuresearch.ops import forecast

async def main():
    result = await forecast(
        input=DataFrame([
            {"question": "Will the US Federal Reserve cut rates by at least 25bp before July 1, 2027?"},
            {"question": "Will SpaceX land Starship on the Moon before 2030?"},
        ]),
        forecast_type="binary",
    )
    print(result.data[["question", "probability", "rationale"]])

asyncio.run(main())

Numeric

Percentile estimates (p10 through p90) for a continuous quantity. Requires output_field and units.

result = await forecast(
    input=DataFrame([
        {"question": "What will the price of Brent crude oil be on December 31, 2026?"},
    ]),
    forecast_type="numeric",
    output_field="price",
    units="USD per barrel",
)
print(result.data[["price_p10", "price_p50", "price_p90"]])

Date

Shortened. The full README is on GitHub.

Nothing above is checked by us. What we check is on the safety report.

Everyrow MCP Server: common questions

Is Everyrow MCP Server safe?: Yes, by our scan: it is graded A (85/100). Read the Everyrow MCP Server safety report
How do I install Everyrow MCP Server?: It runs on your machine. Copy the Claude Code, Cursor, VS Code or Claude Desktop config from the install section.
Does Everyrow MCP Server need an API key?: Yes. The registry entry asks for EVERYROW_API_KEY.
Is Everyrow MCP Server maintained?: The last commit was 40 days ago (2026-09-25). The latest release is v0.5.1.
How does Everyrow MCP Server compare with other MCP servers?: safety score 85/100 (higher than 70% of 48,255 servers); tools 16 (the typical server has 7); tools that change things 38% (typical: 0%. Fewer write tools means less an agent can break). Full comparison.