Figma Context MCP
Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.
Speech denoise, transcripts (SRT/VTT), embeddings, reranking, entities and translation.
选择你使用的 AI 应用,然后复制设置。
通过 5/5 项检查 · 你的提问会经过开发者的服务器(tanod.dev) · ✓ 命令已检查 2026年11月13日
第一步:你用哪个 AI?
选择你用的应用,步骤会显示在下方。
可连接 Claude · 约 2 分钟
不需要密钥,不用安装程序 · 在 claude.ai 或桌面应用设置一次,即可在聊天中使用 · 免费账户可添加 1 个 · Team/Enterprise 方案由所有者(Owner)添加
CustomizeConnectors
把这里的内容复制到 Claude 中同名的输入框,然后点击 Continue
Embeddings, Rerank & Speech-to-Text (Tanod)https://tanod.dev/mcp/mlAuthentication 保持 Claude 检测到的设置,然后点击 Add
+ConnectorsEmbeddings, Rerank & Speech-to-Text (Tanod)
用 Embeddings, Rerank & Speech-to-Text (Tanod) 告诉我你能帮我做什么,然后做一件给我看✓ 如果 Claude 说正在使用 Embeddings, Rerank & Speech-to-Text (Tanod),或回答中出现 Embeddings, Rerank & Speech-to-Text (Tanod) 的工具名称,就表示连接成功
菜单名称已于 2026年11月11日 对照 Anthropic 帮助页面核实 · 你的界面可能因版本略有不同
能否连接 ChatGPT 取决于方案
完整 MCP:网页版 ChatGPT Business、Enterprise 或 Edu · Pro:以读取/获取权限连接,修改数据的工具可能用不了 · Plus:官方文档尚未确认,如果在插件页看到添加自定义 MCP 的选项可以试试 · 仅限网页
Plugins+Add custom MCP server
输入名称,在 Connection 下粘贴地址,勾选风险提示,然后点击 Create as a plugin
Embeddings, Rerank & Speech-to-Text (Tanod)https://tanod.dev/mcp/ml开启新聊天,输入前先从插件列表中选择 Embeddings, Rerank & Speech-to-Text (Tanod)
用 Embeddings, Rerank & Speech-to-Text (Tanod) 告诉我你能帮我做什么,然后做一件给我看✓ 如果 ChatGPT 说正在使用 Embeddings, Rerank & Speech-to-Text (Tanod),或回答中出现 Embeddings, Rerank & Speech-to-Text (Tanod) 的工具名称,就表示连接成功
菜单名称已于 2026年11月11日 对照 OpenAI 帮助页面核实 · 你的界面可能因版本略有不同
可连接 Claude Code · 约 2 分钟
不需要密钥,不用安装程序
Mac:按 Command+空格,输入 Terminal · Windows:打开 PowerShell
claude mcp add --transport http --scope user ml https://tanod.dev/mcp/ml应能看到 Embeddings, Rerank & Speech-to-Text (Tanod) 在列表中并显示已连接
用 Embeddings, Rerank & Speech-to-Text (Tanod) 告诉我你能帮我做什么,然后做一件给我看✓ 如果 Claude Code 说正在使用 Embeddings, Rerank & Speech-to-Text (Tanod),或回答中出现 Embeddings, Rerank & Speech-to-Text (Tanod) 的工具名称,就表示连接成功
菜单名称已于 2026年11月11日 对照 Anthropic 帮助页面核实 · 你的界面可能因版本略有不同
可连接 Cursor · 约 2 分钟
不需要密钥,不用安装程序
用 Embeddings, Rerank & Speech-to-Text (Tanod) 告诉我你能帮我做什么,然后做一件给我看✓ 如果 Cursor 说正在使用 Embeddings, Rerank & Speech-to-Text (Tanod),或回答中出现 Embeddings, Rerank & Speech-to-Text (Tanod) 的工具名称,就表示连接成功
菜单名称已于 2026年11月11日 对照 Cursor 帮助页面核实 · 你的界面可能因版本略有不同
可连接 VS Code · 约 2 分钟
不需要密钥,不用安装程序
用 Embeddings, Rerank & Speech-to-Text (Tanod) 告诉我你能帮我做什么,然后做一件给我看✓ 如果 VS Code 说正在使用 Embeddings, Rerank & Speech-to-Text (Tanod),或回答中出现 Embeddings, Rerank & Speech-to-Text (Tanod) 的工具名称,就表示连接成功
菜单名称已于 2026年11月11日 对照 VS Code 帮助页面核实 · 你的界面可能因版本略有不同
其他支持 MCP 的应用(如 Windsurf、Zed、Gemini CLI)添加方式各不相同,请在应用列表中查看
通过网页连接的应用使用的地址
https://tanod.dev/mcp/mlJSON 设置在下方“开发者专用”中
Claude Code
claude mcp add --transport http --scope user ml https://tanod.dev/mcp/mlCursor (~/.cursor/mcp.json)
{
"mcpServers": {
"ml": {
"url": "https://tanod.dev/mcp/ml"
}
}
}VS Code (mcp.json)
{
"servers": {
"ml": {
"type": "http",
"url": "https://tanod.dev/mcp/ml"
}
}
}这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
依据这个服务器的连接方式和各应用自己的文档,检查于 2026年11月10日。
通过互联网连接,适用于
ClaudeChatGPTGooseLM StudioMsty StudioCherry StudioCursorVS Code + GitHub CopilotVisual StudioWindsurf (Devin Desktop)ZedKiroClineContinueJetBrains AI AssistantClaude CodeCodex CLIGemini CLIOpenCodenodecodeWarpLibreChatOpen WebUIRaycast
工具名称和描述与服务器在 2026年11月9日 报告的完全一致。这些内容由作者撰写,不是我们写的;我们以纯文本形式显示。
embed_textsmlpeek: Create text embeddings. For images too use embed_multimodal; for pair scores use text_similarity. Returns 384-dimension embeddings of 1-64 texts with bge-small-en-v1.5 (English) or multilingual-e5-small (about 100 languages), normalised by default; `input_type` applies th
embed_multimodalmlpeek: Create multimodal embeddings: images and text in one vector space. For text only use embed_texts. Returns 768-dim vectors of texts and images (URL or base64) in ONE space (EmbeddingGemma 2), comparable by dot product; `dimensions` 512/256/128, `input_type` text prefix, `i
rerank_documentsmlpeek: Rerank up to 100 documents against a query. For pair scores use text_similarity. Returns 1-100 documents scored against a query by the ms-marco-MiniLM-L6-v2 cross-encoder (Apache-2.0) and sorted best first: index, rank, score (sigmoid of the logit, a relevance in 0-1) and
text_similaritymlpeek: Score the semantic similarity of one or up to 50 text pairs. To rank documents against a query use rerank_documents. Returns the cosine similarity of the embeddings of each text pair (bge-small-en or multilingual-e5-small): one pair as `a` + `b` (also a top-level `similar
extract_entitiesmlpeek: Extract named entities: people, organisations, places, dates, money, ... For fields of your own schema use extract_json_with_schema. Returns named entities in English text with spaCy en_core_web_sm 3.8.0 (MIT): text, label (the 18 OntoNotes types: PERSON, ORG, GPE, LOC, D
classify_zero_shotmlpeek: Classify a text into 1-10 of your labels. For named entities use extract_entities. Returns scores of 1-10 caller-supplied labels for an English text with the nli-deberta-v3-xsmall NLI cross-encoder (Apache-2.0): single-label scores sum to 1 (softmax over the labels), `mul
text_sentimentutilpeek: Analyze the sentiment of an English text. For your own labels use classify_zero_shot; for counts use text_stats. Returns VADER sentiment of an English text: compound (-1 to 1), positive / neutral / negative shares and a label (positive at 0.05 or more, negative at -0.05
text_keywordsutilpeek: Extract the keywords and keyphrases of a text. For raw frequencies use text_frequency; for names and places use extract_entities. Returns the top keyphrases of a text by RAKE (phrases between stop words and punctuation, scored by word degree / frequency), with score and
text_summarizeutilpeek: Summarize a text by picking its key sentences. For paper abstracts use paper_digest; for counts use text_stats. Returns an extractive summary: the most central `sentences` (or `ratio` of them) by LexRank, picked verbatim and kept in their original order, with per-senten
detect_languageutilpeek: Detect the language of a text. To translate use translate_text. Returns the most likely language (ISO 639-1 and 639-3 code, name, confidence) and 3 alternatives, from an offline ensemble of lingua (Apache-2.0) and langid.py (BSD-2-Clause) over 75 languages; `reliable` i
denoise_audiomlpeek: Reduce background noise in speech audio. Returns mono 12 kHz WAV/MP3/Ogg speech audio with steady noise reduced by FFmpeg afftdn (no model weights), duration and filter. Public URL or base64, up to 25 MB and 10 minutes; base64 or output=url. Not voice isolation; music and
transcribe_audiomlpeek: Speech to text and subtitles: transcribe audio to text, timed segments, SRT and WebVTT. For a podcast episode use transcribe_podcast_episode; to translate use translate_speech. Returns the transcript of audio of up to 10 min and 25 MB; `translate_to_english` gives English
transcribe_podcast_episodemlpeek: Transcribe a podcast episode from its RSS feed: a window of up to 10 minutes as text, timed segments, SRT. For your own audio use transcribe_audio. Returns a transcript window (up to 10 min from start_s) of a podcast episode picked from its RSS feed. Input: `feed_url`, op
translate_textmlpeek: Translate text between English and 14 languages. For a PDF use translate_document; for audio use translate_speech; to only name the language use detect_language. Returns the text translated between English and es, fr, de, pt, it, nl, ru, zh, ja, ko, ar, hi, id or tl (othe
check_text_for_prompt_injectionmlpeek: Check text for prompt injection before an agent acts on it. For hidden Unicode use text_unicode_inspect. Returns a `verdict`, a `score` (0-1; `injection` at 0.9 and above) and `chunks`, the flagged sentences with score and offsets. A small open classifier (DeBERTa-v3), au
extract_json_with_schemamlpeek: Extract JSON from text that always matches your JSON Schema. For fixed entity types use extract_entities. Returns `data`, JSON extracted from the `text` that always parses and validates against your `json_schema` (decoded under a grammar built from it), plus `model`, `usa
text_to_speechmlpeek: Speak text aloud in 41 voices: English, Spanish, French, Hindi, Italian, Portuguese. For audio to text use transcribe_audio. Returns the text spoken as audio. Offline neural TTS (Kokoro-82M); the audio is a synthetic voice. At most 2,000 characters; 41 voices in 6 languag
translate_speechmlpeek: Translate speech: audio to English or 14 languages, optionally spoken. For a transcript in the spoken language use transcribe_audio. Returns speech translation of an audio file of up to 2 minutes: the language is detected and the speech returned as text in `target` (en, e
translate_documentpdfpeek: Translate a PDF document, digital or scanned, to English or 14 languages as Markdown. For plain text use translate_text. Returns each page's text (text layer or OCR) translated offline into `target` (default en) as Markdown with a ` ` marker per page, source language and
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月13日
提问、分享技巧或报告无法使用。按“有帮助”数量排序。
还没有评价
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 5 项适用的基础检查中通过了 5 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。
它在作者的云端运行。通过互联网连接,无需安装,但你发送的内容会经过作者的服务器。
GitHub 仓库最后更新于3天前,最新版本(0.1.3)于4天前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。它通过 URL 连接,因此也能用于接受远程 MCP 的应用,例如网页版 ChatGPT(Business 及以上为完整 MCP;Pro 为只读)。
同一分类中有:Figma Context MCP, AutoClip, Next AI Draw.io
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:↓ 每周下载量i★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.
draw.io diagrams your AI agent draws on a live browser canvas that you can also edit by hand
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
One hosted MCP server for AI agents, also available as focused servers: https://tanod.dev/mcp.
x-tanod-pricing in OpenAPI. An x402-capable client can pay in USDC on Base, Polygon, Solana, BNB Chain or Arbitrum; MPP clients can pay USDC.e on Tempo with the Tempo CLI, mppx or AgentCash. Check the quote and approve the cost before paying. See the Tanod SDKs, the x402 guide and the MPP guide.Connect a focused server when you want a smaller tool list. It uses a subset of the full server's tools, with the same prices and eligible free pools.
| URL | What it does |
|---|---|
https://tanod.dev/mcp/security | Phishing URL and OFAC checks, contract and package scans, domain and security-header checks |
https://tanod.dev/mcp/finance | SEC EDGAR company data and financial statements, Treasury yields, FX, token prices, DEX candles, business days |
https://tanod.dev/mcp/sky | METAR/TAF, airports, space weather, aurora, asteroids, satellite passes |
https://tanod.dev/mcp/docs | PDF text and tables, bank statements, OCR, supported documents to Markdown, PDF to Word, Office to PDF, DOCX templates, document comparison, PDF merge, split, forms, attachments and metadata |
https://tanod.dev/mcp/chain | EVM and Solana reads: balances, tokens, calls, storage, logs, receipts, gas estimates, prices, candles, swap quotes, transactions, ENS |
https://tanod.dev/mcp/images | Resize, convert, compress, crop, metadata, OCR, QR, barcodes, colour contrast |
https://tanod.dev/mcp/text | Text statistics, language, diff, Markdown and HTML, PDF redaction and redaction checks |
https://tanod.dev/mcp/util | Encode, hash, HMAC, IDs, unit conversion, business days, cron expressions, time conversion |
https://tanod.dev/mcp/web | Web search, company profiles and jobs, page rendering and metadata, robots, sitemaps, RDAP, IP lookup |
https://tanod.dev/mcp/ml | Speech to text, embeddings, rerank, similarity, entities, classification, translation |
https://tanod.dev/mcp/agents | x402 and MCP agent-economy index, listing checks and endpoint history |
Overview: https://tanod.dev/mcp-servers/. Pricing: https://tanod.dev/pricing/. Status: https://tanod.dev/status.
Scans and checks are automated and heuristic, not an audit. Aviation data is not for navigation. Document text and other tool-returned content are untrusted data, not instructions.
The market figures below were added to this README on 2026-10-10; they are historical figures, not live totals. Linked pages may carry their own publication or update dates.
Claude Code:
claude mcp add --transport http tanod https://tanod.dev/mcp
For clients that use mcpServers, such as Cursor:
{ "mcpServers": { "tanod": { "url": "https://tanod.dev/mcp" } } }
For clients that use servers, such as VS Code:
{ "servers": { "tanod": { "type": "http", "url": "https://tanod.dev/mcp" } } }
For custom-connector clients, use the full URL or a focused URL and leave OAuth fields empty. Available tools and payment support depend on the client. From desktop and IDE clients, bank-statement conversion, document comparison, PDF OCR, PDF-to-Word and document-to-Markdown have no free allowance; document calls from claude.ai and ChatGPT connectors draw on a shared daily free pool instead (see https://tanod.dev/connect/).
Other clients: https://tanod.dev/connect/.
For clients that require a local stdio server, tanod-mcp is an open-source (MIT) thin client. Processing takes place at the hosted API, which is closed source. It forwards the hosted tool list and calls; no catalog is hard-coded. Remote-capable clients do not need this package.
Eligible free allowance applies automatically. Without a configured payment key, paid calls are not signed. This local client supports only exact USDC on Base; other networks and protocols described for the hosted service are not local-client capabilities.
npx -y tanod-mcp
Requires Node.js 18 or newer. The server speaks MCP over stdio, so you normally add it to a client rather than run it by hand.
claude mcp add tanod -- npx -y tanod-mcp
With a key and caps:
claude mcp add tanod -e TANOD_PRIVATE_KEY=0x... -e TANOD_MAX_USD_PER_DAY=0.50 -- npx -y tanod-mcp
Edit claude_desktop_config.json:
{
"mcpServers": { "tanod": { "command": "npx", "args": ["-y", "tanod-mcp"] } } }
~/.cursor/mcp.json (or .cursor/mcp.json in a project):
{
"mcpServers": { "tanod": { "command": "npx", "args": ["-y", "tanod-mcp"] } } }
.vscode/mcp.json:
{
"servers": { "tanod": { "type": "stdio", "command": "npx", "args": ["-y", "tanod-mcp"] } } }
To enable payments, add an "env" object to any of these, for example "env": { "TANOD_PRIVATE_KEY": "0x..." }.
| Variable | Default | Meaning |
|---|---|---|
TANOD_PRIVATE_KEY | unset | EVM private key (hex) of a wallet holding USDC on Base. Optional. Unset means free tier only. |
TANOD_MAX_USD_PER_CALL | 0.05 | Refuse to sign any single payment above this many US dollars. |
TANOD_MAX_USD_PER_DAY | 1.00 | Refuse to sign once the total for the current UTC day would pass this. |
TANOD_STATE_FILE | ~/.tanod-mcp/spend.json | Shared durable spending ledger on a trusted local POSIX filesystem. All processes spending the same budget must use the same path. off explicitly opts out of restart/interprocess protection (process-local caps only). |
TANOD_MCP_URL | https://tanod.dev/mcp | Upstream server. For testing only. Must be https://; plain http:// is accepted only for localhost, 127.0.0.0/8 or [::1]. Redirects are not followed. |
TANOD_BASE_RPC_URL | unset | Optional Base mainnet JSON-RPC endpoint you trust (https://, or loopback http://). Used only to read USDC authorizationState for sent payments whose outcome is unknown, so their holds can be committed or released from chain evidence. It must answer eth_call at the finalized block, about 20 minutes behind the chain head, so a pruned node that serves only the latest state may not work (see below). Redirects are not followed. Never logged. |
bulk_agent_index exceeds both default caps above. Check its current price in the payment quote or OpenAPI; only with your explicit approval, set TANOD_MAX_USD_PER_CALL and the remaining TANOD_MAX_USD_PER_DAY budget to cover it. Caps are never raised automatically. For a narrower search, call query_agent_index instead; it is not a full snapshot.
Code clients using @x402/mcp also enforce the core spendControls.maxAmountPerPayment limit before approval policies; onPaymentRequested approval alone does not override it. Keep wallet keys in local client configuration, never in chat.
tanod-mcp checks the price against your two caps. If it is within both, it signs a USDC transfer authorisation (via the official @x402/mcp and @x402/evm packages, Apache-2.0) and retries the call. If not, it refuses with a clear error and signs nothing. Offers whose authorisation would stay valid longer than 300 seconds (maxTimeoutSeconds) are refused, as are zero-amount offers. Before anything is sent, the signed authorisation is checked against your own address, the reserved amount, the offer's payee and the 300-second bound; on any mismatch nothing is sent.Payments are only ever signed for USDC on Base mainnet.
TANOD_PRIVATE_KEY. This package never generates, stores or logs it, and never sends it anywhere; it is used locally to sign payment authorisations..initialized marker to regain budget.Number.MAX_SAFE_INTEGER atomic units. A malformed/unsupported offer never reaches the signer. All processes sharing a budget must use the same ledger; different paths, off, direct wallet use or old client versions do