FutureSearch MCP Server

Install

Works with Claude Code, Codex, VS Code, Cursor, Windsurf, Claude Desktop. Read the repository before you give any tool access to your data.

npx agentmarket install connector/futuresearch-futuresearch-mcp

About

Use cases: deep-research, data-analysis

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Permissions

What this server can do and what it asks for, from its tool list, install config and code. Checked Oct 25, 2026.

Tools

9 read · 12 write · 1 delete

Secrets

1 (API keys, tokens or passwords)

Install scripts

None found

Runs as

Python package

Tools (22)

Read from the source code; the running server may differ. Descriptions are the server’s own words; hidden characters are shown as [U+…].

• futuresearch_agentRun Web Research Agents

  Run web research agents on each row of a CSV file. The dispatched agents will search the web, read pages, and return the requested research fields for each row. Agents run in parallel to save time and are optimized to find accurate answers at minimum cost. `task` describes WHAT to research in natural language. `response_schema` defines the OUTPUT STRUCTURE as a JSON Schema. If omitted, results default to a single {"answer": string} field. Pass it whenever you need typed or multi-field output. Do NOT describe desired output columns only in `task` — the schema is what controls the output struc…

• futuresearch_balanceCheck Account Balanceread-only

  Check the current billing balance for the authenticated user. Returns the account balance in dollars. Use this to verify available credits before submitting tasks.

• futuresearch_browse_listsBrowse Reference Listsread-only

  Browse available reference lists of well-known entities. Includes company lists (S&P 500, FTSE 100, Russell 3000, sector breakdowns like Global Banks or Semiconductor companies), geographic lists (all countries, EU members, US states, major cities), people (billionaires, heads of state, AI leaders), institutions (top universities, regulators), and infrastructure (airports, ports, power stations). Use this when the user's analysis involves a well-known group that we might already have a list for. Returns names, fields, and artifact_ids to pass to futuresearch_use_list. Call with no parameter…

• futuresearch_cancelCancel a Running Taskcan change or delete data

  Cancel a running futuresearch task. Use when the user wants to stop a task that is currently processing.

• futuresearch_classifyClassify Rows

  Deprecated: Classify each row of a dataset into one of the provided categories. Uses web research that scales to the difficulty of the classification. Each row is assigned exactly one of the provided categories. Examples: - "Classify each company by its primary industry sector" with categories ["Technology", "Finance", "Healthcare", "Energy"] - "Is this company founder-led?" with categories ["yes", "no"] - "Classify by Koppen climate zone" with categories ["tropical", "arid", "temperate", "continental", "polar"] Output columns added: the ``classification_field`` column (default: ``classific…

• futuresearch_decisionDecision

  Forecast a decision: the outcome under each option, the user's or anyone else's. Causal decision support, e.g. "If I fund this organization at $0 / $300k / $2M, will it ship its study by 2027?" (binary), "…how many researchers will it hire?" (numeric), or "…when will it ship?" (date). Each row states the outcome question, and ``alternatives_field`` names a column holding that row's mutually exclusive alternatives as a JSON array (2-50 entries; a binary "do X / don't do X" decision is the 2-alternative case). The outcome is forecast under each alternative as its own hypothetical, all alternati…

• futuresearch_dedupeDeduplicate Rows

  Deprecated: Remove duplicate rows from a CSV file using semantic equivalence. Dedupe identifies rows that represent the same entity even when they don't match exactly. The duplicate criterion is semantic and LLM-powered: agents reason over the data and, when needed, search the web for external information to establish equivalence. Examples: - Dedupe contacts: "Same person even with name abbreviations or career changes" - Dedupe companies: "Same company including subsidiaries and name variations" - Dedupe research papers: "Same work including preprints and published versions" This function s…

• futuresearch_forecastForecast

  Forecast questions about the future using deep research. The ``forecast_type`` selects what kind of outcome you are forecasting: - **binary** (default): Forecasts probability (0-100) for YES/NO questions. Output columns: ``probability`` (int, 0-100) and ``rationale`` (str). - **numeric**: Forecasts percentile estimates for continuous numeric questions. Requires ``output_field`` (e.g. ``"price"``) and ``units`` (e.g. ``"USD"``). Output columns: ``{output_field}_p10`` through ``{output_field}_p90`` (float), ``units`` (str), and ``rationale`` (str). - **date**: Forecasts date percenti…

• futuresearch_list_session_tasksList Tasks in a Sessionread-only

  List all tasks in a session with their IDs, statuses, and types. Use this to find task IDs for a session so you can display previous results with mcp__display__show_task(task_id, label).

• futuresearch_list_sessionsList Sessionsread-only

  List futuresearch sessions owned by the authenticated user (paginated). Returns session names, IDs, and timestamps. Use this to find past sessions or check what's been run. Results are paginated — 25 sessions per page by default.

• futuresearch_mergeMerge Two Tables

  Deprecated: Join two CSV files using intelligent entity matching. Merge combines two tables even when keys don't match exactly. Uses LLM web research and judgment to identify which rows from the first table should join those in the second. left = the table being enriched (ALL its rows appear in the output). right = the lookup/reference table (its columns are appended to matches). IMPORTANT defaults — omit parameters when unsure: - merge_on_left/merge_on_right: only set if you expect exact string matches on the chosen columns or want to draw agent attention to them. Fine to omit. - relatio…

• futuresearch_multi_agentMulti-Agent Parallel Research

  Deep parallel research: deploys multiple agents on different angles, then synthesizes. Use this when either (a) completeness matters — you're trying to find all items matching a criteria (e.g. "all AI startups in Europe") and a single agent would have poor recall, or (b) depth matters — the answer benefits from parallel investigation across genuinely distinct angles (sources, geographies, methodologies) that one agent would weight unevenly. For list-generation tasks especially, directing agents at different slices (by region, by vertical, by time period) dramatically improves coverage before …

• futuresearch_progressCheck Task Progressread-only

  Check progress of a running task. Blocks briefly to limit the polling rate. After receiving a status update with partial results, briefly comment on the new rows for the user, then immediately call futuresearch_progress again (passing the cursor from this response) unless the task is completed or failed.

• futuresearch_rankScore and Rank Rows

  Deprecated: Score and sort rows in a CSV file based on any criteria. Dispatches web agents to research the criteria to rank the entities in the table. Conducts research, and can also apply judgment to the results if the criteria are qualitative. `task` describes how to score each row in natural language. `response_schema` optionally defines extra output columns as a JSON Schema. If omitted, only the score column is returned. Do NOT describe desired output columns only in `task` — the schema is what controls the output structure. Examples: - "Estimate this drug's peak annual sales in billion…

• futuresearch_request_upload_urlRequest Upload URL

  Request a presigned URL to upload a local CSV file. Use this to upload a file from your local filesystem or sandbox. This is the recommended way to ingest local files in HTTP mode. Steps: 1. Call this tool with the filename (and optionally session_id to add to an existing session) 2. Execute the returned curl command to upload the file 3. Parse the JSON response to get the artifact_id and session_id 4. Pass the artifact_id to any processing tool (futuresearch_agent, etc.)

Signals

Stars

57

Forks

9

Open issues

1

Contributors

14

Weekly downloads

632

Last commit (this folder)

Oct 5, 2026 (25 days ago)

Last release

Oct 5, 2026 (25 days ago)

Last package publish

Oct 5, 2026 (25 days ago)

From GitHub (fetched Oct 24, 2026) and the package registry.

Details

Registry name

io.github.futuresearch/futuresearch-mcp

Version

0.27.0

Auth

API key

Packages

pypi futuresearch-mcp

License

MIT

Repository

github.com/futuresearch/futuresearch-python

Website

github.com/futuresearch/futuresearch-python/tree/main/futuresearch-mcp

First seen

Oct 24, 2026

Last checked

Oct 24, 2026

Source

Official MCP Registrygithub-graphql