All Installation Methods

Platform

Method

Claude.ai with MCP

Go to Settings → Connectors → Add custom connector.
Enter "FutureSearch" for the name. For the remote MCP URL, use https://mcp.futuresearch.ai/mcp. Then click Add.
Go to Settings → Capabilities.
Enable Code execution and file creation.
Enable network egress. This allows Claude to use FutureSearch to process files you've uploaded. You can set the domain allowlist to All domains. Or you can specifically allow *.futuresearch.ai.

Try asking Claude:

Using FutureSearch's lists, tell me which US companies are most pro-AI.

Claude Code with MCP

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

Then launch Claude Code and authenticate with Google:

claude
/mcp → select FutureSearch → Authenticate

No API key needed. Try asking:

Which AI models had the biggest safety implications when released?

Full guide →

Claude Code with Plugin

The plugin bundles an MCP server and a skill that guides Claude to write Python SDK code for advanced pipelines.

claude plugin marketplace add futuresearch/futuresearch-python
claude plugin install futuresearch@futuresearch

Then launch Claude Code and authenticate:

claude
/mcp → select FutureSearch → Authenticate

No API key needed. Try asking:

Which AI models had the biggest safety implications when released?

Full guide →

Python SDK with pip

pip install futuresearch

Requires an API key:

export FUTURESEARCH_API_KEY=sk-cho-...

Getting Started → | API Reference →

Dependencies: Python 3.12+ and pip.

Python SDK with uv

uv add futuresearch

Requires an API key:

export FUTURESEARCH_API_KEY=sk-cho-...

Getting Started → | API Reference →

Dependencies: Python 3.12+ and uv.

Codex with Skills

Ask Codex in natural language:

>>> codex
>>> Install the skill from github.com/futuresearch/futuresearch-python found under skills/futuresearch-python

Or install manually:

python ~/.codex/skills/.system/skill-installer/scripts/install-skill-from-github.py \
  --repo futuresearch/futuresearch-python --path skills/futuresearch-python

Restart Codex to pick up the new skill.

Important: be sure to supply your API key when launching Codex:

export FUTURESEARCH_API_KEY=sk-cho...
codex

Official Docs

Codex with MCP

Add FutureSearch to your Codex MCP config (requires uv):

[mcp_servers.futuresearch]
command = "uvx"
args = ["futuresearch-mcp"]

[mcp_servers.futuresearch.env]
FUTURESEARCH_API_KEY = "${FUTURESEARCH_API_KEY}"

Or use the CLI:

codex mcp add futuresearch --env FUTURESEARCH_API_KEY=${FUTURESEARCH_API_KEY} -- uvx futuresearch-mcp

Config file location:

User scope: ~/.codex/config.toml
Project scope: .codex/config.toml

Important: either insert your API key when creating the config file, or supply the key when launching Codex:

export FUTURESEARCH_API_KEY=sk-cho...
codex

Official Docs

Gemini with Skills

Install the skill directly from GitHub:

gemini skills install https://github.com/futuresearch/futuresearch-python --path skills/futuresearch-python

Use --scope workspace to install to .gemini/skills/ (project-level) instead of ~/.gemini/skills/ (user-level).

Then enable skills within the CLI:

/settings > Preview Features > Enable
/settings > Agent Skills > Enable
/skills enable futuresearch-python
/skills reload

Official Docs

Gemini with MCP

Add via CLI (requires uv):

gemini mcp add -e FUTURESEARCH_API_KEY=$FUTURESEARCH_API_KEY futuresearch uvx futuresearch-mcp

Or add manually to ~/.gemini/settings.json (user) or .gemini/settings.json (project):

{
  "mcpServers": {
    "futuresearch": {
      "command": "uvx",
      "args": ["futuresearch-mcp"],
      "env": {
        "FUTURESEARCH_API_KEY": "$FUTURESEARCH_API_KEY"
      }
    }
  }
}

Official Docs

Gemini with Plugin

This installs both the MCP server and skills together.

gemini extensions install https://github.com/futuresearch/futuresearch-python --ref main

When prompted with Would you like to attempt to install via "git clone" instead?, type Y to confirm.

Then enable the extension:

gemini extensions enable futuresearch [--scope <user or workspace>]

To use skills, enable them within the CLI:

/settings > Preview Features > Enable
/settings > Agent Skills > Enable
/skills enable futuresearch-python
/skills reload
/model > Manual > gemini-3-pro-preview

Official Docs

Cursor with Skills

Open Cursor Settings → Rules
In the Project Rules section, click Add Rule
Select Remote Rule (Github)
Enter: https://github.com/futuresearch/futuresearch-python.git

Official Docs

Cursor with MCP

Or add manually to your MCP config (requires uv):

{
  "mcpServers": {
    "futuresearch": {
      "command": "uvx",
      "args": ["futuresearch-mcp"],
      "env": {
        "FUTURESEARCH_API_KEY": "${env:FUTURESEARCH_API_KEY}"
      }
    }
  }
}

Config file location:

macOS: ~/.cursor/mcp.json
Windows: %USERPROFILE%\.cursor\mcp.json

All Installation Methods

Platform

Method

Claude.ai with MCP

Go to Settings → Connectors → Add custom connector.
Enter "FutureSearch" for the name. For the remote MCP URL, use https://mcp.futuresearch.ai/mcp. Then click Add.
Go to Settings → Capabilities.
Enable Code execution and file creation.
Enable network egress. This allows Claude to use FutureSearch to process files you've uploaded. You can set the domain allowlist to All domains. Or you can specifically allow *.futuresearch.ai.

Try asking Claude:

Using FutureSearch's lists, tell me which US companies are most pro-AI.

Full guide →

Claude Code with MCP

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

Then launch Claude Code and authenticate with Google:

claude
/mcp → select FutureSearch → Authenticate

No API key needed. Try asking:

Which AI models had the biggest safety implications when released?

Full guide →

Claude Code with Plugin

The plugin bundles an MCP server and a skill that guides Claude to write Python SDK code for advanced pipelines.

claude plugin marketplace add futuresearch/futuresearch-python
claude plugin install futuresearch@futuresearch

Then launch Claude Code and authenticate:

claude
/mcp → select FutureSearch → Authenticate

No API key needed. Try asking:

Which AI models had the biggest safety implications when released?

Full guide →

Python SDK with pip

pip install futuresearch

Requires an API key:

export FUTURESEARCH_API_KEY=sk-cho-...

Getting Started → | API Reference →

Dependencies: Python 3.12+ and pip.

Python SDK with uv

uv add futuresearch

Requires an API key:

export FUTURESEARCH_API_KEY=sk-cho-...

Getting Started → | API Reference →

Dependencies: Python 3.12+ and uv.

Codex with Skills

Ask Codex in natural language:

>>> codex
>>> Install the skill from github.com/futuresearch/futuresearch-python found under skills/futuresearch-python

Or install manually:

python ~/.codex/skills/.system/skill-installer/scripts/install-skill-from-github.py \
  --repo futuresearch/futuresearch-python --path skills/futuresearch-python

Restart Codex to pick up the new skill.

Important: be sure to supply your API key when launching Codex:

export FUTURESEARCH_API_KEY=sk-cho...
codex

Official Docs

Codex with MCP

Add FutureSearch to your Codex MCP config (requires uv):

[mcp_servers.futuresearch]
command = "uvx"
args = ["futuresearch-mcp"]

[mcp_servers.futuresearch.env]
FUTURESEARCH_API_KEY = "${FUTURESEARCH_API_KEY}"

Or use the CLI:

codex mcp add futuresearch --env FUTURESEARCH_API_KEY=${FUTURESEARCH_API_KEY} -- uvx futuresearch-mcp

Config file location:

User scope: ~/.codex/config.toml
Project scope: .codex/config.toml

Important: either insert your API key when creating the config file, or supply the key when launching Codex:

export FUTURESEARCH_API_KEY=sk-cho...
codex

Official Docs

Gemini with Skills

Install the skill directly from GitHub:

gemini skills install https://github.com/futuresearch/futuresearch-python --path skills/futuresearch-python

Use --scope workspace to install to .gemini/skills/ (project-level) instead of ~/.gemini/skills/ (user-level).

Then enable skills within the CLI:

/settings > Preview Features > Enable
/settings > Agent Skills > Enable
/skills enable futuresearch-python
/skills reload

Official Docs

Gemini with MCP

Add via CLI (requires uv):

gemini mcp add -e FUTURESEARCH_API_KEY=$FUTURESEARCH_API_KEY futuresearch uvx futuresearch-mcp

Or add manually to ~/.gemini/settings.json (user) or .gemini/settings.json (project):

{
  "mcpServers": {
    "futuresearch": {
      "command": "uvx",
      "args": ["futuresearch-mcp"],
      "env": {
        "FUTURESEARCH_API_KEY": "$FUTURESEARCH_API_KEY"
      }
    }
  }
}

Official Docs

Gemini with Plugin

This installs both the MCP server and skills together.

gemini extensions install https://github.com/futuresearch/futuresearch-python --ref main

When prompted with Would you like to attempt to install via "git clone" instead?, type Y to confirm.

Then enable the extension:

gemini extensions enable futuresearch [--scope <user or workspace>]

To use skills, enable them within the CLI:

/settings > Preview Features > Enable
/settings > Agent Skills > Enable
/skills enable futuresearch-python
/skills reload
/model > Manual > gemini-3-pro-preview

Official Docs

Cursor with Skills

Open Cursor Settings → Rules
In the Project Rules section, click Add Rule
Select Remote Rule (Github)
Enter: https://github.com/futuresearch/futuresearch-python.git

Official Docs

Cursor with MCP

Or add manually to your MCP config (requires uv):

{
  "mcpServers": {
    "futuresearch": {
      "command": "uvx",
      "args": ["futuresearch-mcp"],
      "env": {
        "FUTURESEARCH_API_KEY": "${env:FUTURESEARCH_API_KEY}"
      }
    }
  }
}

Config file location:

macOS: ~/.cursor/mcp.json
Windows: %USERPROFILE%\.cursor\mcp.json