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search-boost-mcp

Multi-engine web search MCP server for coding agents. One CLI install wires it into Cursor, Cursor CLI, Codex, Claude Code, Grok Build, and Antigravity.

search-boost family

Project

For

Link

search-boost (this repo)

Cursor · Codex · Claude · Grok · Antigravity via MCP

you are here

dsh-search-boost

DeepSeek Harness bundle plugin

GitHub · npm

pi-search-boost

pi extension

GitHub · npm

Search engines are vendored in lib/search/ (originally from dsh-search-boost): on the free layer, Bing, DuckDuckGo, Yahoo, and Exa-free run in parallel; the api layer adds Antigravity CLI (when available) and whichever keyed Tavily / Brave / Exa engines you configure (one key is enough; all three recommended for best fusion). Also included: X/Twitter fallback, Jina page fetch, and deep-research rounds.

中文文档 → README_zh.md


Requires Node ≥ 22.13.

npm install -g search-boost-mcp
search-boost setup          # interactive: keys → layer → agents
# or non-interactive:
search-boost install -y     # all detected agents

Restart each agent after install so MCP reloads.

Upgrade

Already using search-boost-mcp? Update the global CLI, then refresh agent configs (keys/layer under ~/.search-boost/ are kept):

npm install -g search-boost-mcp@latest
search-boost install -y                 # all detected agents
# or pick targets, e.g. Grok one-step (plugin + config when grok on PATH):
search-boost install -t grok -y --auto-allow
search-boost doctor

Restart each agent after reinstall. Config lazy-migrates from older flat ~/.search-boost-*.json paths on first write.

One-liners by agent

search-boost install -t cursor -y
search-boost install -t codex,claude -y --auto-allow
search-boost install -t grok -y --auto-allow   # plugin + config when grok CLI on PATH
search-boost install -t antigravity --workspace --auto-allow -y

Preview without writing: search-boost install --dry-run -y

Verify install

search-boost doctor          # health checks (offline, pass/warn/fail)
search-boost doctor --json   # machine-readable report for CI/scripts
search-boost status          # install dashboard (keys, layer, agents)

Exit codes: 0 healthy · 1 failure (or warnings with --strict) · 2 warnings only.

Optional: search-boost doctor --probe adds live search smoke (needs network; Phase 2).

Then confirm in your agent:

Agent

Quick check

Cursor

Settings → MCP → search-boost connected; tools listed

Cursor CLI

Same MCP entry in ~/.cursor/mcp.json

Codex

codex session lists mcp__search-boost__* tools

Claude Code

MCP panel shows search-boost; tools callable without deny prompt (if --auto-allow)

Grok Build

grok mcp doctor search-boost · grok inspect

Antigravity

MCP config includes search-boost; restart IDE after install

If tools appear but calls fail, run search-boost serve in a terminal to see startup errors.

Install flags (quick reference)

Flag

Effect

-t, --target

Which agent(s) to wire (cursor, codex, claude, grok, antigravity, cursor-cli, auto, all)

-y, --yes

Non-interactive: skips keys/layer wizard, uses --target=auto, implies --auto-allow and --replace-native

-t without -y

Still non-interactive for that target and still replaces native search by default — but does not imply --auto-allow; add it explicitly if you want no permission prompts

--auto-allow

Pre-approve search-boost MCP tools in agent config (Cursor CLI allowlist, Codex default_tools_approval_mode, Claude/Grok/Antigravity permission rules) so the agent does not prompt every session

--replace-native / --keep-native

Disable or keep built-in web search where the agent supports a switch (Codex web_search, Claude WebSearch). Default is replace when non-interactive

--scope user|project|all

Grok only: user (~/.grok), project (.grok/ in cwd), or both on uninstall

--skip-grok-plugin

Grok only: skip bundled grok plugin install; still writes config.toml, rule, and skill

--dry-run

Print actions without writing files

For full onboarding (API keys + layer choice), run search-boost setup or search-boost install without -y.

Uninstall

search-boost uninstall -t codex -y
search-boost uninstall -t cursor,codex,claude -y

Uninstall removes only search-boost-owned blocks (marked MCP entries, skills, hooks, permission rules). Where the agent supports it, native web search is restored (Codex top-level web_search, Claude WebSearch deny) unless you used --keep-native at install time or had pre-existing unmarked settings. Config files created solely for search-boost are unlinked when empty after cleanup. For Grok, plugin removal via grok plugin uninstall is best-effort (warns and continues if the CLI is missing or uninstall fails). Preview: --dry-run.


Related MCP server: gemini-search-mcp

What you get

MCP tool

Purpose

fused_search

Multi-engine parallel search, dedupe, cross-ranking

fetch_page

Full page text (Jina + HTML fallback, optional focus)

x_search

X/Twitter keyword / user / thread

deep_research

One round per call — repeat with suggested_queries until gaps empty, then synthesize (~3 rounds max)

search_layer

Show or set free (keyless) vs api (keyed engines)

search_stats

Cache hits, engine availability, diagnostics

Also: resource search-boost://policy · prompt search_routing

Layers

  • free — Bing + DuckDuckGo + Yahoo + Exa-free; no API keys.

  • api — free-layer engines plus Antigravity CLI (when available) and any of Tavily / Brave / Exa that you configure (one key works; all three recommended for best cross-engine fusion)

Keys: search-boost config keys~/.search-boost/config/keys.json (flat ~/.search-boost-keys.json and legacy ~/.dsh-search-boost-keys.json still read; or env TAVILY_API_KEY, BRAVE_API_KEY, EXA_API_KEY). Optional routing: enabledEngines: ["exa"] or "engines": { "brave": { "enabled": false } } in the keys file.

Config layout: runtime data lives under ~/.search-boost/config/ (keys, layer, xauth), cache/ (xguest token), state/ (Antigravity workspace registry). First write lazy-migrates from flat ~/.search-boost-*.json and legacy ~/.dsh-* files (old copies kept). Override base: SEARCH_BOOST_HOME; per-file: SEARCH_BOOST_*_FILE.

Obtain keys: Tavily · Brave Search API · Exa

X/Twitter auth (optional): improves official x_search when credentials are present. Stored at ~/.search-boost/config/xauth.json (flat/legacy paths still read) or via XAI_API_KEY. Configure with search-boost config x (see CLI cheat sheet). MCP /x-login and search-boost config x write the same local copy. Override file path: SEARCH_BOOST_XAUTH_FILE.

search-boost config x --show              # xauth status
search-boost config x --import-grok       # import grok CLI login
search-boost config x --set-xai-key KEY   # store XAI API key
search-boost config x --logout            # remove local copy

Config file overrides: SEARCH_BOOST_KEYS_FILE, SEARCH_BOOST_LAYER_FILE, SEARCH_BOOST_XAUTH_FILE (optional env vars pointing at custom paths).


CLI cheat sheet

Command

What it does

search-boost

Interactive TUI

search-boost setup

Onboarding (keys + layer + install)

search-boost install / uninstall

Wire MCP + prompts into agents

search-boost serve

Run MCP stdio server (used by agents)

search-boost status

Keys, layer, X credentials, per-agent configured state

search-boost doctor [--quick|--probe] [--json] [--strict]

Config/agents/engine health checks with pass/warn/fail

search-boost config keys|layer|x|search

Keys, default layer, X auth, native-search replace

search-boost print <agent>

Print MCP snippet without writing

search-boost agents

Machine-readable agent list

Install flags: -t cursor,codex,…|auto|all · -y (non-interactive; implies --auto-allow + --replace-native) · --dry-run · --auto-allow (pre-approve MCP tools — see table above) · --replace-native / --keep-native · --scope user|project|all (Grok) · --skip-grok-plugin (Grok) · --workspace (Antigravity .agents/)


Supported agents

Agent

MCP config

Also installs

Cursor IDE

~/.cursor/mcp.json

hook, skill

Cursor CLI

~/.cursor/mcp.json (same surface as IDE)

hook, skill (CLI variant), optional CLI auto-allow

Codex CLI

~/.codex/config.toml

AGENTS.md, skill

Claude Code

~/.claude.json

CLAUDE.md, skill, permissions

Grok Build

~/.grok/config.toml

rule, skill, bundled grok-plugin (when grok on PATH)

Antigravity

~/.gemini/config/mcp_config.json

AGENTS.md, GEMINI.md, skill, optional workspace

Prompts use model-discretion wording (search when you choose — not forced every turn). See agents/ for per-agent templates.

Native web search: With --replace-native (default when non-interactive), Codex gets a marked top-level web_search = "disabled" in config.toml (never inside [mcp_servers.*]); Claude gets an ownership-marked WebSearch deny in settings.json. Uninstall removes only search-boost-owned entries and restores native search when safe. Cursor / Antigravity rely on skill + hook preference only. Grok native browse is left on.

Cursor + Cursor CLI: Both targets share one ~/.cursor/ surface. Installing -t cursor,cursor-cli merges IDE + CLI prompts into a single write; uninstall clears the shared surface.

Antigravity + agy CLI: On the api layer, the optional Antigravity CLI engine (agy on PATH) joins medium and complex fused_search tiers only — not simple lookups. It depends on local sign-in and platform quota; timeouts are ~45s.

Grok Build: search-boost install -t grok -y --auto-allow runs grok plugin install <bundled grok-plugin> --trust when the Grok CLI is on PATH, then writes config.toml, rule, and skill. If grok is not on PATH, the plugin step is skipped with a warning and the config install still proceeds. Use --skip-grok-plugin for config/rule/skill only. Re-install is idempotent for [permission] blocks (marked or legacy); uninstall strips search-boost-owned permission lines. If [ui] permission_mode = "always-approve", --auto-allow skips injecting [permission]. The plugin's .mcp.json uses portable npx; config.toml uses resolveMcpLaunch() (local node when developing from a clone) — both can coexist. Manual plugin install: grok plugin install ./grok-plugin --trust (advanced) → grok-plugin/README.md.


Troubleshooting

Symptom

What to try

Is search-boost healthy?

search-boost doctor — pass/warn/fail verdict; --json for scripts

Install fails immediately

Node ≥ 22.13 (node -v); upgrade if older

MCP server missing in agent

Re-run install, restart the agent, check search-boost status

Tool calls blocked / approval every turn

Re-install with --auto-allow, or approve once in the agent UI

No results / empty engines

search-boost doctor — check layer/keys/engine checks; free needs no keys; api needs at least one keyed engine via search-boost config keys or env vars (all three recommended)

Network/proxy issues

Phase 2: search-boost doctor --probe (not yet implemented)

MCP won't start

search-boost doctormcp_launch_command, node_version; then search-boost serve

Grok plugin MCP won't start

grok mcp doctor search-boost; ensure npx and network access work

grok fails on config.toml parse

Duplicate [permission] — run search-boost install -t grok -y --auto-allow

Antigravity agy never runs

Requires api layer, agy on PATH, and complexity medium/complex — not simple

Timeouts / fetch errors

Corporate proxy or firewall may block Bing/DDG/Jina; try search-boost serve locally to read stderr


Development

git clone https://github.com/Mr-remon219/search-boost.git
cd search-boost && npm install
npm run check && npm run test:install && npm run smoke
node cli.mjs install --dry-run -y

Local clone installs write node /path/to/cli.mjs serve (not npx). No sibling checkout or SEARCH_BOOST_DSH_ROOT is required.


License

MIT


Links: Issues · dsh-search-boost · pi-search-boost

Friendly link: LINUX DO 社区

Available Tools

6 tools
deep_researchDeep Research (one round)A
Read-only

One research round: complex fused search + coverage analysis + gaps + suggested follow-up queries. Call repeatedly with suggested_queries until gaps is empty, then synthesize with citations.

ParametersJSON Schema
NameRequiredDescriptionDefault
layerNo
queryYes
roundNoResearch round number (auto-increments when omitted)
queriesNo
recencyNo
max_sourcesNo

Output Schema

ParametersJSON Schema
NameRequiredDescription
gapsYes
queryYes
roundYes
tookMsYes
sourcesYes
suggested_queriesYes

TDQS

A4.1/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The annotations already indicate readOnly/openWorld/not destructive, and the description adds meaningful behavioral context: the tool is one round of an iterative workflow, returns gaps with suggested follow-up queries, and should be concatenated into a cited synthesis. This gives the agent useful expectations beyond the annotation flags.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, front-loaded with the core capability, and contains no filler. The iterative call pattern and final synthesis are stated economically and clearly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description captures the essential workflow: perform one research round, follow the suggested follow-ups, stop when gaps are empty, then synthesize with citations. Since an output schema exists, return-value detail is not required. The main gap is the poor explanation of the parameter semantics, but overall the high-level usage context is sufficiently complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is very low (17%), so the description must compensate, but it only vaguely refers to 'suggested_queries' without explicitly mapping it to the 'queries' parameter. The meaning of 'layer', 'recency', 'round', and 'max_sources' is left entirely to the schema, which is insufficient given the low coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it performs 'one research round' combining 'complex fused search + coverage analysis + gaps + suggested follow-up queries.' This is a specific multi-phase verb-resource description that also distinguishes the tool from sibling tools like fetch_page and x_search by emphasizing iterative research coverage.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives explicit usage guidance: 'Call repeatedly with suggested_queries until gaps is empty, then synthesize with citations.' This clearly explains the iteration and termination conditions. However, it does not explicitly compare against sibling tools or state when not to use it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

fetch_pageFetch PageA
Read-only

Fetch readable page text via Jina Reader with local HTML fallback. Use focus to filter paragraphs.

ParametersJSON Schema
NameRequiredDescriptionDefault
urlYeshttp(s) URL to fetch
focusNoKeep paragraphs matching these terms (~90% token savings)

Output Schema

ParametersJSON Schema
NameRequiredDescription
urlYes
viaYes
tookMsYes
contentYes
truncatedNo
word_countYes

TDQS

A4/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate readOnlyHint=true and destructiveHint=false. The description adds behavioral context: use of Jina Reader with a local HTML fallback (indicating reliability strategy) and focus filtering for token savings. No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences: first states the core function and method, second adds the optional focus feature. No redundant or wasted content. Front-loaded effectively.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given low complexity (2 params), rich schema descriptions, annotations, and an output schema, the description covers the main behavior and the focus filter. It could mention error handling or timeout but is sufficient for a simple fetch tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, with both parameters already well-described ('http(s) URL to fetch', 'Keep paragraphs matching these terms (~90% token savings)'). The description only echoes 'Use focus to filter paragraphs', adding no new meaning.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states 'Fetch readable page text via Jina Reader with local HTML fallback', which is a specific verb+resource. It distinguishes from sibling search tools (e.g., fused_search, deep_research) by targeting a single URL rather than performing searches.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit when-to-use or alternatives are provided. However, the description implies usage for fetching content from a specific URL, and sibling tool names (search tools) suggest the context. Guidance is implied but not stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

search_layerSearch LayerA

Switch or show search layer. free = free — keyless engines only (bing + ddg + yahoo + exa-free). api = api — keyless legs plus one or more keyed tavily/brave/exa (all three recommended).

ParametersJSON Schema
NameRequiredDescriptionDefault
layerNo

TDQS

A4.4/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The annotations already indicate this is not read-only and not destructive; the description adds meaningful context by explaining what switching to 'free' vs 'api' changes about the underlying engine composition. It does not detail side effects or persistence, but for a simple configuration switch, the disclosed behavior is sufficient. No contradiction with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely compact, with the core action front-loaded in the first sentence and the mode meanings packed into the second. Every clause adds value, and there is no redundant repetition of the title or schema.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a one-parameter optional configuration tool with no output schema, the description covers the main decision space well. The only notable gap is 'show' behavior not being described in the mode definitions, but the overall tool is simple enough that this does not severely compromise completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description carries the burden of explaining parameters. It successfully explains two of the three enum values ('free' and 'api') with concrete engine lists. The 'show' value is only implied by the opening verb and lacks explicit detail about what it displays or returns.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb+resource combination, 'Switch or show search layer,' which clearly identifies the action and target. It also distinguishes this tool from the sibling search tools by focusing on layer configuration rather than executing searches, and the mode definitions reinforce the purpose.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives clear context for when to choose each layer value: 'free' for keyless engines only, 'api' for adding keyed engines, and 'show' to inspect the current layer. It does not explicitly state when not to use the tool or name alternatives, but the mode explanations provide practical selection guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

search_statsSearch StatsA
Read-only

Diagnostics: cache hits/misses, tier counts, engine availability, recent searches.

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

Output Schema

ParametersJSON Schema
NameRequiredDescription
layerYes
recentYes
enginesYes
xSourceYes
cacheHitsYes
startedAtYes
xOfficialYes
tierCountsYes
cacheMissesYes

TDQS

A4.1/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true and destructiveHint=false, so the behavioral profile is clear. The description adds useful context about what diagnostics are included but does not mention rate limits, permissions, or other traits beyond the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, concise line with no wasted words. It is front-loaded with 'Diagnostics:' to immediately signal purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given zero parameters, an output schema, and clear sibling tool names (all search functions), the description is complete for an agent to understand the tool's purpose and when to use it.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

There are zero parameters, so baseline is 4. The description adds value by listing the diagnostic categories, which is the only source of information about what the tool returns.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly indicates this is a diagnostics tool for search statistics, listing specific categories (cache hits/misses, tier counts, etc.). It distinguishes itself from sibling tools like fused_search and deep_research, which are search functions.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implicitly suggests use for diagnostics, but does not explicitly state when to use this tool versus alternatives (e.g., 'use this to check cache health, not for searching'). No exclusion criteria or sibling differentiation is provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. 2 tool updatesv0.1.6
    • Changeddeep_research1 field changed
      • addedInput schema / properties / round
        Added value: +{
        +  "description": "Research round number (auto-increments when omitted)",
        +  "minimum": 1,
        +  "type": "integer"
        +}
    • Changedfused_search4 fields changed
      • addedOutput schema / properties / engineStats
        Added value: +{
        +  "additionalProperties": {
        +    "additionalProperties": false,
        +    "properties": {
        +      "errors": {
        +        "type": "number"
        +      },
        +      "note": {
        +        "type": "string"
        +      },
        +      "used": {
        +        "type": "boolean"
        +      }
        +    },
        +    "required": [
        +      "used",
        +      "errors"
        +    ],
        +    "type": "object"
        +  },
        +  "type": "object"
        +}
      • addedOutput schema / properties / enginesRequested
        Added value: +{
        +  "items": {
        +    "type": "string"
        +  },
        +  "type": "array"
        +}
      • addedOutput schema / properties / enginesUsed
        Added value: +{
        +  "items": {
        +    "type": "string"
        +  },
        +  "type": "array"
        +}
      • addedOutput schema / properties / warnings
        Added value: +{
        +  "items": {
        +    "type": "string"
        +  },
        +  "type": "array"
        +}
  2. 6 tool updatesv0.1.2
    • First observeddeep_research
    • First observedfetch_page
    • First observedfused_search
    • First observedsearch_layer
    • First observedsearch_stats
    • First observedx_search

TDQS

A3.9/5.0
Disambiguation5/5

Each tool has a clear, distinct purpose: fetch_page extracts text from URLs, fused_search performs general web search, search_layer manages API layer configuration, deep_research runs multi-step research, x_search targets Twitter-specific queries, and search_stats provides diagnostics. No two tools overlap in intent, making selection unambiguous.

Naming Consistency4/5

All names use lowercase snake_case and follow a pattern of modifier+noun (e.g., fused_search, deep_research, x_search, search_stats), though fetch_page uniquely uses a verb+noun structure. This minor deviation is easily readable and does not create confusion.

Tool Count5/5

With 6 tools, the set is well-scoped for a search/boost utility. Each tool contributes to distinct functional areas: fetching, multi-engine search, configuration, deep research, social search, and diagnostics, justifying its inclusion without bloating the surface.

Completeness4/5

The tool surface covers the full search lifecycle: input (fused_search, x_search), processing (deep_research includes analysis and follow-ups), content access (fetch_page), configuration (search_layer), and observability (search_stats). Minor omissions like image search or trend analysis are not critical for the core domain.

Maintenance

ActivityMaintained
ResponsivenessNo issues

Resources

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