Moltline Research Desk

com.moltlinestudio由 moltlinestudio.com 發布官方發布者v1.2.0更新於 Oct 24, 2026

7 research navigation, thesis, note-taking and citation skill products. 6 of 8 free.

發布方自己的服務:Moltline Business Suite

已驗證Streamable HTTP可網頁執行知識與記憶資料與分析

概覽

AI 產生的概覽

Moltline Research Desk 是託管型 MCP 伺服器,提供 7 個研究、論文、筆記與引用技能產品,以及免費的統計輔助工具。

可以做什麼
  • 瀏覽產品線並載入某產品的免費入門技能說明
  • 憑授權載入完整產品人設與全部技能,或載入單一指定技能
  • 依 APA 7、MLA 9 或 Chicago 作者-年份格式產生引用
  • 描述數值資料集,提供集中趨勢、離散度、四分位數與離群值
  • 計算調查所需樣本數,以及平均值的信賴區間
適用情境
適合需要結構化研究與寫作技能說明、引用格式化,或快速完成描述統計與樣本數計算的情境,不必另裝統計工具。
執行需求
遠端 Streamable HTTP 端點;免費工具無需帳號或憑證。付費工具需 Moltline 授權,透過 MOLTLINE_LICENSE 環境變數設定,並以 X-Moltline-License 請求標頭送出。僅支援 stdio 的用戶端可使用橋接腳本。
安裝前請注意
8 個工具中 6 個免費;完整產品與完整技能工具需購買授權。授權屬機密,應透過環境變數而非命令列參數傳入。免費層為匿名存取,呼叫不與帳號綁定。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Moltline Research Desk,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Web executable,透過 Streamable HTTP。 遠端服務在工作區中設定後即可從網頁執行環境執行。

交給代理程式安裝

把這段提示詞貼上到 Claude Code、Codex、Cursor 等代理程式,或 SourceWeft 對話中。代理程式會讀取該伺服器的安裝指南,先向你展示發布者、端點和登入方式,經你同意後再把它新增到你的客戶端。金鑰不會寫進任何命令。

閱讀 https://sourceweft.com/mcp/com.moltlinestudio%2Fresearch/install.md,並按其中說明把這個 MCP 伺服器接入我的客戶端。修改任何設定之前,先告訴我它的發布者、端點和登入方式,等我確認。不要把 API 金鑰寫進命令或我會提交的檔案;問我金鑰應從哪裡取得。

檢視代理程式所依據的安裝指南

其他 MCP 客戶端

把它新增到你客戶端的 mcpServers 設定中。

{
  "mcpServers": {
    "moltline-research-desk": {
      "type": "http",
      "url": "https://mcp.moltlinestudio.com/research"
    }
  }
}

README

moltline-mcp

A thin, dependency-free stdio bridge to Moltline Studio's fleet of 22 hosted MCP servers.

Most modern MCP clients can connect to the fleet directly over Streamable HTTP, no install needed (see Direct connection below). This bridge exists for clients that only speak the stdio transport: it proxies newline-delimited JSON-RPC between your client and the hosted server, verbatim, with no telemetry and no dependencies beyond the Python 3.9+ standard library.

  • 160 tools across 22 servers; 110 are free.
  • Free tier: no registration, no account, no credentials. Connect and call tools immediately.
  • Premium tools are unlocked with a Moltline license. Set MOLTLINE_LICENSE in your MCP client's environment; the bridge sends it as the X-Moltline-License header and never writes it to argv, URLs or logs. See auth.md.
  • Independently checked by MCPize on the direct endpoints (scans of 5–6 September 2026: 6 A+, 15 A, 1 B+; scores 89–98). All 22 servers score 100 on clarity, 100 on reliability and 100 on trust, 95 on protocol and 87 on safety; the one finding raised on every server is that the free tier accepts anonymous access (which is the point of it), and the spread between servers sits in MCPize's "Market" dimension (a crowded category). Each server's MCPize listing links its own public result.

Find it on: Smithery · MCPize · Glama · Clawmart · MCP Registry

The fleet

ServerToolsWhat it does
catalog10Search 138 agent skills and personas by plain-language job; preview any product.
codereview7Risk-scan a diff, flag AI-generated-code tells, find secrets, report complexity.
govern8Audit an MCP config or SKILL.md for over-broad scope and prompt-injection risk.
timeops5Business days, meeting overlap, recurrence expansion, deadline and SLA math.
data7Paste-your-data analytics: CSV profiling, A/B tests, correlation, growth, cohorts.
humanizer5Find AI-isms with evidence, fingerprint a writing voice, measure burstiness.
business830 finance, bookkeeping, legal-ops and SMB operations persona-skill products.
creator820 blogging, brand-voice, copywriting, video and social persona-skill products.
educator78 curriculum, classroom, accommodations and exam-prep persona-skill products.
outbound87 outreach, sequencing, deliverability, call-coaching and CRM-hygiene products.
personal920 inbox, calendar, travel, meals and family-logistics persona-skill products.
research87 research navigation, thesis, note-taking and citation persona-skill products.
skillmd-lint6Lint a SKILL.md for frontmatter, structure, secrets and size. All tools free.
merchant6Commerce arithmetic: processor fees, charge-to-net, invoice totals, proration.
shipping6Dimensional weight, parcel fit, landed cost, freight class, rate cards.
shopify6Check a product CSV, URL handles, variant matrices and metafield keys.
dropship6Dropshipping unit economics: margin, lead time, SKU mapping, price ladders.
recall6A portable knowledge-graph memory you pass in and get back. No database.
vision6Image header probing, bbox conversion, resize plans, color and detection math.
regclock9Incident-reporting deadlines from the legal text (EU CRA, NIS2, DORA, GDPR, UK GDPR, HIPAA, SEC 8-K), cited.
taxlots8Crypto cost basis: parse exchange CSVs, lint, match transfers, FIFO/LIFO/HIFO lots, Form 8949 rows, 1099-DA diff.
optimize11OR-Tools routing, 3-D packing, 1-D/2-D cutting, knapsack and shift rostering with stated limits.

Machine-readable discovery: api-catalog · per-server card at https://mcp.moltlinestudio.com/<server>/.well-known/mcp/server-card.json · fleet health.

Direct connection (preferred)

If your MCP client supports Streamable HTTP (Claude Desktop, Claude Code, Cursor, and most current clients do), point it straight at the hosted endpoint (nothing to install):

json
{  "mcpServers": {    "moltline-timeops": {      "type": "http",      "url": "https://mcp.moltlinestudio.com/timeops"    }  }}

Swap timeops for any slug in the table above.

The stdio bridge (for stdio-only clients)

Install

Run directly (recommended): the bridge is a single stdlib-only file, so a clone is all you need:

bash
git clone https://github.com/GarphenGate/moltline-mcp.gitpython3 moltline-mcp/moltline_mcp.py timeops   # any of the 22 slugs; default: catalog

Docker: see Docker below if you prefer a container.

A PyPI package is planned; until then, use the methods above.

Client configuration

Point your MCP client at the script with an absolute path:

json
{  "mcpServers": {    "moltline-timeops": {      "command": "python3",      "args": ["/absolute/path/to/moltline-mcp/moltline_mcp.py", "timeops"]    }  }}

Or run it through Docker (after docker build -t moltline-mcp .):

json
{  "mcpServers": {    "moltline-timeops": {      "command": "docker",      "args": ["run", "-i", "--rm", "moltline-mcp", "timeops"]    }  }}

CLI

text
python3 moltline_mcp.py [server] [--timeout SECONDS] [--list] [--version]
  • server: one of the 22 slugs (default catalog); anything else fails fast with the valid list.
  • --timeout: per-request timeout in seconds (default 300, or env MOLTLINE_TIMEOUT).
  • --list: print the server slugs and exit.
  • Env MOLTLINE_BASE_URL: override the fleet base URL (for testing).
  • Env MOLTLINE_LICENSE: your Moltline license, sent as the X-Moltline-License header to unlock premium tools. Omit it and the bridge runs free-tier only.
  • Env MOLTLINE_DEBUG=1: diagnostic logging on stderr (stdout stays protocol-clean). The license is never logged; debug output reports only whether one is configured.

Docker

The bridge also runs containerized (stdio in, network egress to the fleet required):

bash
docker build -t moltline-mcp .docker run -i --rm moltline-mcp timeops   # any of the 22 slugs; default: catalog

See Client configuration for the matching mcpServers entry.

How it works

One process per server connection. Each JSON-RPC message read from stdin is POSTed to https://mcp.moltlinestudio.com/<server>; JSON and SSE-framed responses are relayed back to stdout as newline-delimited JSON. The bridge tracks the server-assigned Mcp-Session-Id and echoes the negotiated MCP-Protocol-Version, per the Streamable HTTP transport spec. It never inspects, stores, or reports your traffic.

Tests

The bridge ships with an offline test suite - no network, no dependencies:

bash
python -m unittest -v

Twenty-two tests cover the parts that actually break in a transport bridge: newline-delimited framing, SSE event splitting (multiple events, multi-line data: payloads, a trailing event with no blank line, comments and named events), session-id capture and reuse, protocol-version negotiation on initialize only, and error relay - a JSON-RPC error document is passed through verbatim, anything else becomes a well-formed -32603. CI runs them on Python 3.9, 3.12 and 3.13, plus a Docker build and container smoke test.

Access and licensing

  • Free tier: anonymous. No registration or credentials; all free tools work immediately.
  • Premium: unlocked with a Moltline license purchased (human-in-the-loop) at moltlinestudio.com. Set MOLTLINE_LICENSE in the environment and the bridge forwards it as the X-Moltline-License request header. It is deliberately not a command-line flag: argv is world-readable through ps. It is never placed in a URL and never logged. Details: auth.md.

Links

License

MIT © 2026 Moltline Studio

來源:README.md,提交 bbf91e4

工具

8

list_products

List Products

List every product in the Research Desk line with its included skills. FREE. Takes no arguments. Returns a list of 7 product objects, each {"slug": "thesis-advisor", "name": ..., "tagline": ..., "skills": ["Skill A", ...], "free_skill": "Gateway Skill Name"}. Use the returned slug values with get_free_skill, get_full_product, or get_full_skill. Returns metadata only - no persona text and no skill instructions. Use when the caller wants to see what this server covers. Not for keyword search across the whole 138-product catalog, which the catalog server's search_catalog does, and not for instructions the caller can act on (get_free_skill). Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"}. Every call is read-only and idempotent, so after correcting the input it is always safe to retry.

無需輸入參數。

get_free_skill

Get Free Skill

Load a product's free gateway skill with its complete instructions. FREE. Typical input {"slug": "thesis-advisor"} returns {"slug": ..., "skill": "<skill name>", "instructions": "<full skill text>"}. Returns exactly one skill - the product's free gateway skill - chosen automatically from the slug, with no plan required. Use when the caller wants usable instructions immediately. Not for the product's other skills: those are named and need get_full_skill with a skill_name, which requires a paid plan. Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"} (for example {"error": "unknown slug '<value>'. Use list_products."}). Every call is read-only and idempotent, so after correcting the input it is always safe to retry.

輸入參數slug必填

format_citation

Format Citation

Format a citation in APA 7, MLA 9, or Chicago author-date style. FREE. Typical input {"style": "apa", "authors": ["Curie, Marie"], "year": 1911, "title": "Radium and radioactivity", "container": "Century Magazine"} returns {"style": "apa", "citation": "Curie, M. (1911). Radium and radioactivity. Century Magazine.", "note": "..."}. Use when the source details are already known and only the formatting is missing. Not for finding or verifying a source. Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"} (for example {"error": "style must be apa, mla, or chicago"}). Every call is read-only and idempotent, so after correcting the input it is always safe to retry.

輸入參數urlyear必填style必填title必填authors必填accessedcontainerpublisher

get_full_product

Get Full Product

Load one product in full: its persona plus every paid skill. PREMIUM (license). Typical input {"slug": "thesis-advisor"} returns {"slug": ..., "name": ..., "persona": "<persona text>", "skills": [{"name": ..., "instructions": ...}, ...], "free_skill": {...}}. Returns persona plus every skill for one product. Use when the caller wants the whole product. Not for a single skill (get_full_skill) and not for a free look, which list_products and get_free_skill provide with no plan. Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"} (for example {"error": "unknown slug '<value>'"}). Every call is read-only and idempotent, so after correcting the input it is always safe to retry.

輸入參數slug必填

get_full_skill

Get Full Skill

Load one paid skill's complete instructions from a product. PREMIUM (license). Typical input {"slug": "thesis-advisor", "skill_name": "Outline Builder"} returns {"slug": ..., "skill": ..., "instructions": "<full skill text>"}. Returns one named skill, selected by skill_name. Use when the caller wants one specific paid skill. Not for the free gateway skill, which get_free_skill returns with no plan, and not for every skill at once (get_full_product). Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"} (for example {"error": "unknown slug '<value>'"}). Every call is read-only and idempotent, so after correcting the input it is always safe to retry.

輸入參數slug必填skill_name必填

stats_describe

Stats Describe

Describe a numeric dataset: center, spread, quartiles, and outliers. FREE. Typical input {"numbers": [12, 15, 14, 90, 13]} returns {"n": 5, "mean": 28.8, "median": 14.0, "std_dev": ..., "min": 12, "max": 90, "q1": ..., "q3": ..., "iqr_outliers": [90], "skew": "right (mean > median)"}. Use as a first summary of one numeric dataset. Not for interval estimates (confidence_interval) and not for planning a study (sample_size). Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"} (for example {"error": "no numbers"}). Every call is read-only and idempotent, so after correcting the input it is always safe to retry.

輸入參數numbers必填

sample_size

Sample Size

Calculate the survey sample size needed for a confidence level and margin. FREE. Uses maximum variance (p=0.5) with a finite-population correction when population is given. Typical input {"population": 5000, "confidence_pct": 95, "margin_pct": 5} returns {"required_sample": 357, "assumptions": "p=0.5 (max variance), random sampling"}. Use before collecting data, to size a survey. Not for analyzing data already collected (stats_describe, confidence_interval). Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"} (for example {"error": "confidence_pct must be 90, 95, or 99"}). Every call is read-only and idempotent, so after correcting the input it is always safe to retry.

輸入參數margin_pctpopulationconfidence_pct

confidence_interval

Confidence Interval

Compute a confidence interval for a mean (normal approximation). FREE. Typical input {"mean": 72.4, "std_dev": 8.1, "n": 64, "confidence_pct": 95} returns {"mean": 72.4, "margin_of_error": 1.9845, "interval": [70.4155, 74.3845], "note": "..."}. Use on data already collected, for a mean. Normal approximation, so it is unreliable on very small or heavily skewed samples. Not for proportions or two-group comparisons - the data server's ab_test compares two proportions. Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"} (for example {"error": "confidence 90/95/99, n>=2, std_dev>=0"}). Every call is read-only and idempotent, so after correcting the input it is always safe to retry.

輸入參數n必填mean必填std_dev必填confidence_pct

版本歷史

1
  1. v1.2.0最新Sep 16, 2026

評分

已滿足適用檢查項的 100%

該評分衡量此收錄條目的完整程度,依據註冊中心條目、端點與公開來源計算得出。它不是對伺服器本身的評價,也不表示伺服器安全或目前可用:可連通性是帶日期的檢查結果,評分也不包含安裝量或使用者評價。

  • 近 30 天內可連通必需25 分
  • 已宣告認證方式必需10 分
  • 已列出工具必需15 分
  • 描述必需15 分
  • 圖示10 分
  • 文件15 分
  • 授權條款10 分

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