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Add Tavily Tool

OrganizationPopular
nanocoai
add-tavily-tool

Add Tavily Search and Extract as keyless remote MCP tools for selected NanoClaw agent groups. Use when installing Tavily web search or URL extraction without an API key.

Overview

Publishernanocoai
Repositorynanoclaw
Skill nameadd-tavily-tool
Stars
30.9K
Forks
12.8K
Bundled files
3
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by nanocoai on GitHub. Read the source before you install it.

Installation

Install the Add Tavily Tool AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/nanocoai/nanoclaw/tree/main/.claude/skills/add-tavily-tool
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/nanocoai/nanoclaw.git /tmp/nanoclaw
mkdir -p .claude/skills
cp -r /tmp/nanoclaw/.claude/skills/add-tavily-tool .claude/skills/add-tavily-tool
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Add Tavily Tool in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Add Tavily Tool on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Add Tavily Tool is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Add Tavily Tool

Install the pinned mcp-remote bridge in the agent image and register Tavily's remote MCP server for each selected agent group. The MCP server supplies its tool descriptions and input schemas at runtime.

The registered server exposes:

  • mcp__tavily__tavily_search
  • mcp__tavily__tavily_extract

The registration is provider-agnostic: any provider with MCP support picks it up (Claude, OpenCode, and Codex all do). Groups on the Claude provider already have the built-in WebSearch and WebFetch tools (container/agent-runner/src/providers/claude.ts), so the skill adds the most for groups on other providers, and for Tavily's structured extraction anywhere.

Phase 1: Pre-flight

Check whether the bridge is already in the image manifest, then list the groups:

bash
grep -n '"mcp-remote"' container/cli-tools.json || true
ncl groups list

Ask which agent groups should receive Tavily. If mcp-remote is already present at a pinned version, reuse the existing entry instead of adding a second one.

Phase 2: Install the MCP bridge

Add this object to the top-level array in container/cli-tools.json when an entry named mcp-remote is not already present:

json
{
  "name": "mcp-remote",
  "version": "0.1.38"
}

Keep the JSON valid and limit the entry to the two fields shown; this package does not require a native build-script opt-in.

Copy the dependency guard into the host test tree:

bash
cp .claude/skills/add-tavily-tool/tavily-manifest.test.ts src/tavily-manifest.test.ts

Build the image and run the guard:

bash
./container/build.sh
pnpm exec vitest run src/tavily-manifest.test.ts

The manifest is the only source-backed integration point. Per-group MCP registration is runtime state stored through ncl, so it has no in-tree line for a registration test to guard.

Phase 3: Register Tavily

config add-mcp-server and groups restart are approval-gated. Run from inside a container they return approval-pending immediately; that is not an error. Wait for the admin's approval and the follow-up system message before moving on to Phase 4.

For each selected <group-id>, register one server named tavily:

bash
ncl groups config add-mcp-server \
  --id <group-id> \
  --name tavily \
  --command mcp-remote \
  --args '["https://mcp.tavily.com/mcp/","--transport","http-only","--enable-proxy","--header","X-Tavily-Access-Mode:keyless","--header","X-Client-Name:nanoclaw","--ignore-tool","tavily_crawl","--ignore-tool","tavily_map","--ignore-tool","tavily_research"]' \
  --env '{}'

The keyless header enables Tavily's IP-based allowance. The client-name header attributes calls to NanoClaw. The tool filters leave only Search and Extract available.

Restart each selected group:

bash
ncl groups restart \
  --id <group-id> \
  --message "Tavily Search and Extract are installed. Run one Tavily search with max_results 1 and report whether it succeeds."

Phase 4: Verify

Confirm the stored configuration contains one tavily server with both headers:

bash
ncl groups config get --id <group-id>

Then check the selected agent's test response. The call must use mcp__tavily__tavily_search. Tavily Crawl, Map, and Research must not appear in the Tavily namespace.

Phase 5: Install the upgrade path

The keyless allowance is shared by every group on the host, so it can run out. Install standing instructions so the agent offers the paid-key upgrade at that moment instead of dead-ending. For each selected group:

  1. Resolve the OneCLI dashboard URL the user's browser can reach:

    bash
    docker inspect onecli --format '{{range .Config.Env}}{{println .}}{{end}}' | grep '^APP_URL='

    If the value is a loopback or container-bridge address (127.0.0.1, 172.17.0.1, host.docker.internal), ask the operator which URL they open the OneCLI dashboard at, suggesting http://127.0.0.1:10254 as the default. A public or tailnet APP_URL needs no question.

  2. Gate the deeplink: curl -fs <dashboard-url>/connections/custom must return HTTP 200. If it does not (older OneCLI without the prefill route), replace step 2 of the template with: "Ask an operator to run, on the host: onecli secrets create --name tavily --type generic --host-pattern mcp.tavily.com --header-name Authorization --value-format 'Bearer {value}' --file <key-file>".

  3. Substitute {{ONECLI_DASHBOARD_URL}} in upgrade-instructions.md with the resolved URL and write the block into groups/<group-folder>/instructions.prepend.md: replace an existing <!-- tavily-upgrade:start --> to <!-- tavily-upgrade:end --> block in place, append otherwise. Do not write into groups/<group-folder>/CLAUDE.md; it is regenerated at spawn and appended blocks are lost.

  4. Have the operator open the composed deeplink once and confirm the create dialog loads with host mcp.tavily.com prefilled. If they supplied a public URL while APP_URL was a loopback address, suggest setting the public URL in the OneCLI dashboard (Settings, Instance) so future links stay stable.

  5. Restart each selected group: ncl groups restart --id <group-id>.

Keyless limit

If Tavily returns HTTP 429 or monthly_cap_reached_bonus_eligible, the keyless allowance is exhausted. With Phase 5 installed the agent offers the upgrade on its own: the user creates a free API key and stores it through the prefilled dashboard link; the key lands in the OneCLI vault and the gateway injects it into the bridge's requests. The agent then re-registers the server without the X-Tavily-Access-Mode:keyless header and restarts the group. The agent never sees the key.

Troubleshooting

  • command not found: mcp-remote: rebuild the image, then restart the group.
  • Tavily tools are absent: verify the group has a tavily MCP entry, then restart it.
  • Crawl, Map, or Research appears: restore all three --ignore-tool pairs.
  • 429 or monthly_cap_reached_bonus_eligible: the keyless allowance is exhausted; see Keyless limit for the OneCLI upgrade path.
  • The agent reports exhaustion but never offers the upgrade: check that groups/<group-folder>/instructions.prepend.md contains the tavily-upgrade block (Phase 5) and restart the group. A session that already discussed the limit keeps reasoning from that history; /clear starts a clean one.

Removal

See REMOVE.md for the idempotent removal procedure.

References

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Add Tavily Tool AI skill do?

Add Tavily Search and Extract as keyless remote MCP tools for selected NanoClaw agent groups. Use when installing Tavily web search or URL extraction without an API key.

Why use Add Tavily Tool on TypingMind?

Because you install it once and use it with any model. Add Tavily Tool is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Add Tavily Tool in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/nanocoai/nanoclaw/tree/main/.claude/skills/add-tavily-tool. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Add Tavily Tool?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Add Tavily Tool?

As many as you like. As long as a model supports skills, you can use Add Tavily Tool with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Add Tavily Tool AI skill free?

Yes. It is published on GitHub by nanocoai under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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