Moltline Research Desk

com.moltlinestudio由 moltlinestudio.com 发布官方发布者v1.2.0更新于 Oct 24, 2026

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

发布方自己的服务:Moltline Business Suite

已验证Streamable HTTP可网页运行知识与记忆数据与分析

概览

AI 生成的概览

Moltline Research Desk 是一个托管型 MCP 服务器,提供 7 个研究、论文、笔记与引用技能产品,以及免费的统计辅助工具。

可以做什么
  • 浏览产品线并加载某产品的免费入门技能说明
  • 凭许可证加载完整产品人设与全部技能,或加载单个指定技能
  • 按 APA 7、MLA 9 或 Chicago 作者-年份格式生成引用
  • 描述数值数据集,给出集中趋势、离散度、四分位数与离群值
  • 计算调查所需样本量,以及均值的置信区间
适用场景
适合需要结构化研究与写作技能说明、引用格式化,或快速完成描述统计与样本量计算的场景,无需另装统计工具。
运行要求
远程 Streamable HTTP 端点;免费工具无需账号或凭据。付费工具需 Moltline 许可证,通过 MOLTLINE_LICENSE 环境变量设置,并以 X-Moltline-License 请求头发送。仅支持 stdio 的客户端可使用桥接脚本。
安装前请注意
8 个工具中 6 个免费;完整产品与完整技能工具需购买许可证。许可证属于机密,应通过环境变量而非命令行参数传入。免费层为匿名访问,调用不与账号绑定。

安装

在 SourceWeft 中

  1. 打开 控制台中的 Moltline Research Desk,将其添加到工作区。
  2. 为需要使用其工具的对话启用该服务。

Web executable,通过 Streamable HTTP。 远程服务在工作区中配置后即可从网页运行时运行。

交给智能体安装

把这段提示词粘贴到 Claude Code、Codex、Cursor 等智能体,或 SourceWeft 对话中。智能体会读取该服务器的安装指南,先向你展示发布者、端点和登录方式,经你同意后再把它添加到你的客户端。密钥不会写进任何命令。

阅读 https://sourceweft.com/mcp/com.moltlinestudio%2Fresearch/install.md,并按其中说明把这个 MCP 服务器接入我的客户端。修改任何配置之前,先告诉我它的发布者、端点和登录方式,等我确认。不要把 API 密钥写进命令或我会提交的文件;问我密钥应从哪里获取。

查看智能体所依据的安装指南

其他 MCP 客户端

把它添加到你客户端的 mcpServers 配置中。

{
  "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

来源: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.

无需输入参数。

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.

输入参数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.

输入参数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.

输入参数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.

输入参数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.

输入参数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.

输入参数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.

输入参数n必填mean必填std_dev必填confidence_pct

版本历史

1
  1. v1.2.0最新Sep 16, 2026

评分

已满足适用检查项的 100%

该评分衡量此收录条目的完整程度,依据注册中心条目、端点与公开来源计算得出。它不是对服务器本身的评价,也不表示服务器安全或当前可用:可连通性是带日期的检查结果,评分也不包含安装量或用户评价。

  • 近 30 天内可连通必需25 分
  • 已声明认证方式必需10 分
  • 已列出工具必需15 分
  • 描述必需15 分
  • 图标10 分
  • 文档15 分
  • 许可证10 分

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