MCPサーバーを探すためのMCPサーバー。さらに、エージェントフレームワークがツールを呼び出す前に参照できるアドバイザリートラスト判定を提供します。mcpindex.ai から。
エージェントループ内で他のMCPサーバーを発見・比較・インストール・事前チェックできる、そのまま使えるMCPサーバーです。mcpindex.ai をバックエンドとし、公式レジストリのエージェントネイティブなMCPサーバーインデックス（ライブ数は mcpindex.ai/stats で確認）を提供。毎日スクリーニングとドリフト監視を行っています。
ライブサイト · npx mcp-server-mcpindex · リモートMCP · インストールゲート · ドキュメント · 信頼
npm install -g mcp-server-mcpindexこれはディレクトリ / アドバイザリークライアント（推奨、検索、信頼）です。パス内ドリフトゲートはインストールしません。それは curl -fsSL https://mcpindex.ai/install.sh | sh です。
Node 20+ が必要です。stdio で両方のプロトコル世代に対応しています：2026-07-28 リビジョン（server/discover、リクエストごとの _meta エンベロープ）と、現在のすべてのクライアントが使用する initialize ハンドシェイク（2025-11-25 から 2024-10-07 まで）。接続ごとに選択されます。
何もインストールしたくないですか？ mcpindex はホスト型リモートMCPサーバーでもあります。リモートMCPをサポートする任意のクライアント（Claude コネクタ、Cursor など）を次の場所に向けてください：
https://mcpindex.ai/api/mcpストリーミングHTTP、認証情報不要。npm パッケージと同じ6つのツールを提供します。
claude mcp add --scope user mcpindex -- npx -y mcp-server-mcpindex@latestgemini mcp add -s user mcpindex npx -y mcp-server-mcpindex@latestRelated MCP server: filesystem-mcp
~/Library/Application Support/Claude/claude_desktop_config.json に追加：
{
"mcpServers": {
"mcpindex": {
"command": "npx",
"args": ["-y", "mcp-server-mcpindex@latest"]
}
}
}
@latestで最新を維持：これはアドバイザリー発見サーバー（パス内ドリフトゲートではない）なので、バージョン固定はありません。npxは次回ホスト再起動時に最新版を取得します。手動アップグレードは不要です。
Claude Desktop を再起動します。そして次のように尋ねます：
「PDFを読んでS3に書き込めるMCPサーバーを探して」
Claude は recommend_mcp_for_task を呼び出し、インストールコマンド付きの上位3サーバーを返します。
.cursor/mcp.json に追加：
{
"mcpServers": {
"mcpindex": {
"command": "npx",
"args": ["-y", "mcp-server-mcpindex@latest"]
}
}
}Cline の設定に追加：
npx -y mcp-server-mcpindex@latestツール | 説明 |
| 自然言語のタスクを渡します。推論、インストールコマンド、品質スコア付きの上位3サーバーを返します。 |
| レジストリ全体のキーワード + セマンティック検索。オプションのカテゴリフィルター。 |
| サーバー + クライアント（Claude Desktop、Claude Code、Cursor、Gemini CLI、Cline、Zed）の正確なインストールJSON/CLIを取得します。 |
| 2〜5サーバーの並列比較 - 品質スコア、インストールパス、環境変数。 |
| サーバー上の特定ツールに対する呼び出し前のアドバイザリー判定。フェイルクローズド：判定がファイルにない場合は UNVERIFIED を返します。 |
| サーバー上の全ツールにわたる集約された事前フライト判定。 |
check_tool_trust はディレクトリクライアント統合サーフェスです（パス内 mcpindex-gate ではありません）。エージェントフレームワーク（Composio、Mastra、LangChain、DSPy、生のLLMツール呼び出しループ）が、呼び出しをディスパッチする前にアドバイザリースクリーニング判定を要求できるようにします。v1 では REVIEW または UNVERIFIED が表示されます。安全クリアランスではありません。
Mastra を使っていますか？ 姉妹パッケージ
@mcp-index/mastraは、この正確なスクリーニングを既製のbeforeToolCallフックとして提供します。npm i @mcp-index/mastraで配線不要です。
{
"directive": "ALLOW" | "DENY" | "REVIEW" | "UNVERIFIED",
"status": "EVALUATED" | "PARTIAL" | "STALE" | "ERROR",
"granularity": "description-level" | null, // scope of a PARTIAL screen
"dimensions": [
{ "id": "tool_safety", "verdict": "PASS", "severity": "INFO" }
],
"expires_at": "2026-06-30T00:00:00Z",
"honest_limits": [
"conformance_monitored_not_enforced",
"calibrated_false_v1",
"advisory_deployment"
],
"verdict_contract_version": "1.0.0",
"server_id": "github",
"tool_name": "create_pull_request",
"source_url": "https://mcpindex.ai/api/v1/trust/tool/github/create_pull_request",
"fetched_at": "2026-05-28T18:42:11.118Z"
}無料層の判定には、ディレクティブ + ディメンション + 鮮度が含まれます。エビデンス引用、LLM の根拠、チェーン履歴は有料層のサーフェスであり、ここでは意図的に省略されています。
すべての v1 判定には次の3つの注意事項が付属し、ゲートはすべてのディスパッチ決定でこれらを表示するべきです：
conformance_monitored_not_enforced - パブリッシャーは自己申告。mcpindex はドリフトを監視しますが、ネットワーク層でブロックしません。
calibrated_false_v1 - ディメンションの重大度は、実際のインシデントデータに対してまだ較正されていません。
advisory_deployment - 判定はアドバイザリーです。エージェント（またはエージェントをレビューする人間）が意思決定者です。
履歴アンカリング：OTS Bitcoin アンカー履歴。Bitcoin 確定は N=6 確認（約1時間）。約10分で保留。サブウィンドウ精度は主張されており、証明されていません。
import { Client } from '@modelcontextprotocol/sdk/client/index.js';
import { StdioClientTransport } from '@modelcontextprotocol/sdk/client/stdio.js';
const mcpindex = new Client({ name: 'gate', version: '1.0.0' }, { capabilities: {} });
await mcpindex.connect(new StdioClientTransport({
command: 'npx', args: ['-y', 'mcp-server-mcpindex@latest'],
}));
// gateToolCall wraps any agent tool dispatch. Plug it in front of
// the LangChain / DSPy / Mastra / Composio tool-call hook.
async function gateToolCall({ serverId, toolName, invoke, askHuman }) {
const res = await mcpindex.callTool({
name: 'check_tool_trust',
arguments: { server_id: serverId, tool_name: toolName },
});
const verdict = JSON.parse(res.content[0].text);
// Pin the v1 caveats in the audit log no matter what.
audit.log({ verdict, caveats: verdict.honest_limits });
switch (verdict.directive) {
case 'REVIEW':
// Fail-CLOSED to human. Do NOT auto-execute on REVIEW.
// At v1 this is the common screened outcome (semantic-only).
return askHuman({ verdict, action: `${serverId}/${toolName}` });
case 'UNVERIFIED':
// No verdict on file (or upstream unreachable). Fail-CLOSED.
// Recommend human review. Do NOT fail-open to invoke().
return askHuman({
verdict,
action: `${serverId}/${toolName}`,
note: 'No trust verdict on file. Human review required before first use.',
});
case 'ALLOW':
// Reserved in the contract — not produced by the v1 public screen.
// Keep the branch for future conformance-earned ALLOW; do not expect it today.
return invoke();
case 'DENY':
// Reserved in the contract — not produced by the v1 public screen.
throw new Error(
`mcpindex denied ${serverId}/${toolName}: ${JSON.stringify(verdict.dimensions)}`,
);
default:
// Unknown directive. Fail-CLOSED.
return askHuman({ verdict, action: `${serverId}/${toolName}` });
}
}判定エンドポイントに到達できない、404 を返す、タイムアウトする、不正な JSON を返す、またはそのサーバーに対する判定がまだファイルにない場合、check_tool_trust は directive: "UNVERIFIED" + status: "ERROR" を返します。決して黙って ALLOW に変換しません。ゲートコードは UNVERIFIED を「人間のレビューが必要」として扱うべきであり、「問題ない、出荷しよう」とは決して扱わないでください。
status はスクリーニングの完全性に関するテレメトリであり、directive の信頼決定とは異なります：EVALUATED（完全なスクリーニング）、PARTIAL（サーフェスの一部のみ、例：説明レベル - granularity を参照）、STALE（鮮度ウィンドウを過ぎた判定）、ERROR（到達不能 / 判定なし）。PARTIAL スクリーニングが EVALUATED として報告されることはありません。
これはテスト済みです。test/trust.test.mjs を参照してください。
トラストクライアントはプレーンな ES モジュールとしてもエクスポートされています：
import { checkToolTrust, assessServer } from 'mcp-server-mcpindex/src/trust.mjs';
const verdict = await checkToolTrust({
serverId: 'github',
toolName: 'create_pull_request',
});
if (verdict.directive !== 'ALLOW') {
// Hand to a human, log, or block.
}デフォルトでは、呼び出しは https://mcpindex.ai に送信されます。セルフホストする場合は MCPINDEX_API_BASE=... で上書きします。
無料層は 60 req/min/IP にレート制限されています。有料キーは、より高いスループットと完全なエビデンス付き判定（エビデンス引用、LLM の根拠、チェーン履歴）のために近日提供予定です。
mcpindex をエージェントに取り込む3つの方法。異なるサーフェス向け：
パッケージ | インストール | 説明 |
|
| ディレクトリ + アドバイザリースクリーンを MCP サーバーとして提供：タスクでサーバーを検索し、呼び出し前に |
|
| 同じアドバイザリースクリーンを Mastra の |
|
| パス内ドリフトゲート：MCP セッションを |
アドバイザリースクリーン vs ドリフトゲート： このパッケージと @mcp-index/mastra は mcpindex に「このツールは審査済みか？」（ネットワーク判定）を尋ねます。@mcp-index/sdk はローカルで異なる質問をします：「ピンしたときからこのツールの契約は変わったか？」 補完的であり、どれも他に依存しません。
MIT。
ウェブサイト: mcpindex.ai
サーバーを審査: mcpindex.ai/screen
ガイド: タスクに合ったMCPサーバーを見つける
非公式です。Anthropic とは提携していません。
Aggregated pre-flight trust assessment across all tools on an MCP server. Same verdict shape as check_tool_trust. Use for "is THIS server worth integrating?" decisions. v1 advisory; conformance monitored not enforced; verdicts may be UNVERIFIED if not yet probed.
| Name | Required | Description | Default |
|---|---|---|---|
| server_id | Yes | Server slug to assess. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description discloses behavioral traits: advisory nature, conformance monitoring not enforced, and potential UNVERIFIED verdicts. This adds valuable context beyond a simple read operation, though no side effects or auth needs are mentioned.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three concise sentences without redundancy: purpose, use, and behavioral notes. Front-loaded with the core action, efficient and clear.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers purpose, usage guidance, verdict shape, and advisory nature. For a simple one-parameter tool with no output schema, it provides sufficient context, though explicit mention of return format would be slightly better.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'server_id' is described in the schema as 'Server slug to assess.' The description does not add new meaning beyond usage context. With 100% schema coverage, a baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool performs an aggregated pre-flight trust assessment across all tools on a server, using the specific verb 'assess' and resource 'server'. It distinguishes from sibling 'check_tool_trust' by noting aggregation, and clarifies the verdict shape is identical.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states the use case: 'is THIS server worth integrating?' decisions. It also provides context on when to be cautious with 'v1 advisory; conformance monitored not enforced; verdicts may be UNVERIFIED if not yet probed', guiding appropriate reliance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Pre-invocation advisory screen for a specific tool on an MCP server. Returns an advisory verdict object (directive ALLOW | DENY | REVIEW | UNVERIFIED, dimensions, freshness). At v1 the public screen produces REVIEW or UNVERIFIED only — ALLOW/DENY are reserved. Not the in-path gate (mcpindex-gate). Agents SHOULD treat UNVERIFIED as "human review required", never as ALLOW.
| Name | Required | Description | Default |
|---|---|---|---|
| server_id | Yes | Server slug (e.g. "github", "filesystem"). Same id used by search_mcp_servers. | |
| tool_name | Yes | Tool name as exposed by the server (e.g. "create_pull_request"). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It accurately describes behavior: returns advisory verdict with specific fields, v1 only produces REVIEW or UNVERIFIED. Does not mention side effects, but none expected. Could add authentication requirements, but sufficient for a read-only check.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, no fluff. Front-loads purpose, then constraints, then usage guideline. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple two-parameter tool with no output schema, the description covers purpose, return value, version limitations, and usage advice. No gaps for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (both parameters described in schema). Description adds no extra meaning beyond what schema provides. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: a pre-invocation advisory screen for a specific tool. It uses specific verb 'check' and resource 'tool trust', and distinguishes from siblings like assess_server and search_mcp_servers by focusing on a single tool's trust level.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use (pre-invocation advisory) and when not (not the in-path gate). Provides clear directive: treat UNVERIFIED as human review required. Distinguishes from sibling tools effectively.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Side-by-side comparison of 2-5 MCP servers - quality scores, install paths, transport types, env vars.
| Name | Required | Description | Default |
|---|---|---|---|
| slugs | Yes | Server slugs to compare. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses the output content (quality scores, install paths, etc.) but does not mention any side effects, auth requirements, or that it is a read-only operation. It assumes a non-destructive nature, but this is not explicit.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
One sentence encapsulates the core functionality without any wasted words. It is front-loaded with the key action 'Side-by-side comparison' and details the compared attributes.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple one-parameter tool with no output schema, the description is relatively complete by listing the compared attributes. However, it does not mention output format, ordering, or whether results are aggregated, which would enhance completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for the single parameter 'slugs', with min/max items already defined. The description does not add semantic detail beyond what the schema provides, so it meets the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool compares 2-5 MCP servers side-by-side, listing specific attributes (quality scores, install paths, etc.). This distinguishes it from siblings like assess_server (single server) and recommend_mcp_for_task (recommendation).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use for comparing multiple servers but does not explicitly state when to use it versus alternatives or any prerequisites. It could benefit from guidance on when to choose compare_servers over assess_server or search_mcp_servers.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get the exact install command for a given MCP server and client. Returns a JSON block ready to paste into the client config.
| Name | Required | Description | Default |
|---|---|---|---|
| client | Yes | Target client. | |
| server_slug | Yes | Slug of the server (from search_mcp_servers or recommend_mcp_for_task results). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description discloses the tool returns a JSON command ready to paste. It does not mention any side effects or authentication, but for a retrieval tool this is sufficiently transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no wasted words, perfectly front-loaded with the action and output.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with two well-described parameters and no output schema, the description is complete: it explains what it does and what it returns.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and both parameters have descriptions. The description adds marginal value beyond the schema, so baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves the install command for a given server and client, and specifies the output format (JSON block). This distinguishes it from sibling tools like search or recommend.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is implied by the description, but there is no explicit guidance on when to use this tool versus alternatives, nor conditions to avoid usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recommend the best MCP servers for a natural-language task. Returns top 3 ranked picks with reasoning, install commands, and quality scores. Use this when the user asks for the right MCP server for a task they want to do.
| Name | Required | Description | Default |
|---|---|---|---|
| task | Yes | Natural-language description of the task, e.g. "read PDFs and write to S3" or "search GitHub and open a PR". |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses the output structure: 'Returns top 3 ranked picks with reasoning, install commands, and quality scores.' This is sufficient for a read-only recommendation tool. It could mention ranking criteria or data sources for greater transparency, but the current description is clear.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences: the first states purpose and output, the second gives usage guidance. It is front-loaded with key information and contains no superfluous words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, no output schema), the description adequately covers what the tool does and returns. It mentions the top 3 picks, reasoning, install commands, and quality scores. It could be enhanced by referencing sibling tools for alternative uses, but it is sufficiently complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage with a description for the 'task' parameter. The tool description does not add additional examples or constraints beyond the schema's example. Thus, per the baseline, a score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Recommend the best MCP servers for a natural-language task.' It specifies the verb (recommend), resource (MCP servers), and context (natural-language task). This distinguishes it from sibling tools like search_mcp_servers (which lists servers) and assess_server (which evaluates a single server).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says when to use the tool: 'Use this when the user asks for the right MCP server for a task they want to do.' It lacks explicit when-not-to-use or alternatives, but the context is clear enough for most agents.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Keyword + semantic search across the full MCP server registry. Use when the user knows what tool category they want but not which server.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max results (default 10, max 50). | |
| query | Yes | Search query. | |
| category | No | Optional category filter (e.g. database, browser, github, productivity). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description bears full responsibility for behavioral disclosure. It only states the search capability, missing details on read-only nature, authentication, rate limits, or any side effects. Minimal transparency beyond basic function.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the action and purpose. Every word adds value. No redundancy or unnecessary details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple search tool with 3 parameters and no output schema, the description is adequate but has gaps. It does not explain result format, pagination, or search behavior beyond 'keyword + semantic'. Could be more complete given lack of annotations and output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description does not add meaning beyond the schema; it mentions keyword + semantic search but that is already implicit. No additional parameter guidance.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool performs keyword + semantic search across the MCP server registry, with a specific use case ('when the user knows what tool category they want but not which server'). This distinguishes it from sibling tools like assess_server or get_install_command.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit context for when to use the tool, but does not mention when not to use it or list alternatives. The guidance is clear and useful, but lacks exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
v0.3.7assess_servercheck_tool_trustcompare_serversget_install_commandrecommend_mcp_for_tasksearch_mcp_serversScored across 6 tools
Each tool targets a clearly distinct purpose: search, recommend, compare, install, and two levels of trust assessment (server-level and tool-level). Even the trust tools are well-differentiated by scope.
All tool names follow a consistent verb_noun pattern using snake_case: assess_server, check_tool_trust, compare_servers, get_install_command, recommend_mcp_for_task, search_mcp_servers.
With 6 tools covering search, recommendation, comparison, installation, and trust, the number is well-scoped for a server registry/helper. No tools feel redundant or unnecessary.
The set covers the core workflow of finding, evaluating, and installing MCP servers. A minor gap is the lack of a tool to retrieve full metadata for a single server (e.g., description, version), but search and comparison partially fill that need.
Search and install 4,000+ security-scanned MCP servers from inside any MCP-aware AI client.
Search and get install details on MCP servers, right from your agent -- a unified marketplace index.
Search, vet & assemble MCP servers from your agent: verified tools, risk labels, and trust scores.
Capability registry for the agentic economy. Semantic search over verified MCP server listings.
