Cftc Mcp

io.github.mrfentmen由 GitHub 账号 mrfentmen 发布v1.0.2更新于 Nov 6, 2026

Commitments of Traders reports: commercial, fund and small-trader positioning in futures markets.

已验证STDIO仅桌面金融数据与分析

概览

AI 生成的概览

提供美国 CFTC 持仓报告(COT)数据,让助手查询期货市场的持仓、历史、极值与未平仓量。

可以做什么
  • 查询某市场最新的持仓报告,含商业、基金与散户持仓
  • 获取某市场近几周的每周持仓明细,并计算多空与净持仓的平均值
  • 按关键词查找期货市场,并按未平仓量排出领先市场
  • 列出投机净多头与净空头最集中的市场
适用场景
适合需要助手回答美国期货市场投机与商业持仓问题、按未平仓量比较市场,或从公开 CFTC 数据中找出多空拥挤持仓的场景。
运行要求
以本地 stdio 进程运行,通过 npm 包 @mrfentmen/cftc-mcp 安装,需要 Node.js。未声明任何 API 密钥、环境变量或请求头;数据来自公开的 CFTC 报告,通常需要网络访问。
安装前请注意
工具只读取公开数据,未声明任何凭据,不会索取密钥。数据来自每周发布的公开报告,可能滞后于当前行情,应作为参考数据而非交易建议。

安装

在 SourceWeft 中

  1. 打开 控制台中的 Cftc Mcp,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。

Desktop only,通过 STDIO。 STDIO 服务会启动本地进程,因此需要 SourceWeft 桌面宿主。

其他 MCP 客户端

参照 仓库 中的启动说明。

README

awesome-servers

One repo for three families of servers, each subtree keeping its own layout and tooling so it can still be built, run and published on its own.

SubtreeWhat it holdsRun one
mcp/338 TypeScript MCP servers, plus 1107 published packages in published/cd mcp/servers/<slug> && npm install && npm run build
acp/79 Python ACP agentspython3 acp/agents/<name>/agent.py
a2a/37 Python A2A servers plus the shared a2a_kitpython3 a2a/servers/<name>/server.py
watchd/a threshold watcher that runs the feeds between editor sessionspython3 watchd/watchd.py --config conditions.json --loop
site/the published site: registry with search, the public-feed atlas, watchd planshttps://mrfentmen.github.io/awesome-servers/

Most servers read public data with no key of their own; the ones wrapping a vendor API take that vendor's key. Nothing in this repo asks a caller to pay. On 2026-10-17 the licence machinery was removed for good: the per-tool src/license.ts gates are gone from the MCP servers, and the A2A and ACP trees no longer carry the hosted licence-gateway half — the skills that used it now answer with an explicit not-implemented stub. Nothing here asks a caller to pay, and nothing they run is refused with a buy link.

Nothing here is generated: each subtree's README says what its servers read, and every server has its own unit tests (mcp/servers/<slug>/tests, acp/agents/<name>/tests, a2a/servers/<name>/tests) plus a live smoke check (tools/smoke*.py, a2a/tools/smoke_all.py).

Novel and original

Nearly all of this is first-of-its-kind work, not a port of an existing catalogue. Before each server or agent was built, it was checked against the official tool lists (the MCP registries, agentclientprotocol.com's agent list and registry) and a live GitHub search for the same domain, and the research logs record what was found and why it still counted as missing — see mcp/MISSING.md, acp/MISSING.md and a2a/docs/. Highlights:

  • The MCP side holds TypeScript servers, one npm package each, and 1039 published packages under published/; mcp/MISSING.md documents the check that preceded every build: what was searched, what was skipped and why the domain still counted as uncovered.
  • On the ACP side there were zero domain agents before this repo — every agent on the official list was a coding agent. These 79 Python agents are the first non-coding ACP agents, and several use protocol surfaces no other agent uses in production (session/request_permission for dataset reads, fs/write_text_file for a briefing file, session/cancel for a conditional watch, image content blocks, a live SSE push feed), each proved-unused in the wild by search at build time. Two more firsts carry their own proof: the orchestrator is an agent whose feeds are agents — it spawns sibling repo agents as real ACP child processes and merges their answers — and the nyc pack is the first multi-agency city surface.
  • acp/MISSING.md doubles as the public-feed atlas: every keyless feed probed live, with its date, what it answered and whether it still works. The published site renders that table at https://mrfentmen.github.io/awesome-servers/atlas.html.
  • The pattern across all three subtrees is the same thesis: wrap one real, keyless public dataset, answer honestly about what the feed did and did not say, and keep the whole thing small, tested and self-contained.

Publishing

  • MCP servers publish from mcp/servers/<slug> (its own package.json, version and README).
  • ACP and A2A servers are repo-run today (Python, no packaging step).

Built on top of it

Creatures that use this corpus as their world live in the sibling repo mrfentmen/superagents (public, with its own claim-check in MISSING.md):

  • polymath — routes your question to the most fitting agents of this repo, spawns each as a real ACP child process, and merges the answers into one brief with per-row citations; a sibling that fails appears as a named row, never silence. Its registry is a data file and its ranking is deterministic word-scoring, not a model opinion.
  • sentry — one plain sentence ("watch air quality in Denver over 150") becomes a tracked watch: a permission-asked protocol write produces the conditions file this repo's watchd/ obeys unchanged, plus the activation lines. Checks it can author today: air thresholds, quake magnitudes within a radius, river gauges at flood stage.
  • fedora hat guy — the persona agent in his own repo mrfentmen/fedora-hat: says "never miss" and means it — one sentence installs the full crown of watches (air + quakes, gauge-named flood) in one permissioned write, and your other questions are forwarded to the siblings above with every row cited.
  • instink — the instinct agent in his own repo mrfentmen/instink: compiles a skill into a reflex — a matcher plus the answer it fires, with hit/miss counters and honest promotion/demotion. The skill doc stays one step away, never deleted.
  • contextink — the context agent in his own repo mrfentmen/contextink: you say "do this" and it acquires the context from the repo, git, and recent files so you don't have to explain it; asks only the minimal high-information-gain questions when acquisition fails.
  • rewind — the replay agent in his own repo mrfentmen/rewind: replays agent runs and mutates one variable to see what would have happened. Replay + mutate + diff for agent traces.
  • scopink — the scope agent in his own repo mrfentmen/scopink: checks if an action is within the scope of what was asked. Detects scope creep in agent plans.
  • curious — the curiosity agent in his own repo mrfentmen/curious: proactively seeks information it doesn't have. Scans for knowledge gaps, seeks answers, learns facts.
  • bored — the idle agent in his own repo mrfentmen/bored: uses idle time productively. Consolidates memories, explores areas, prepares for tasks.

Point the polymath at a checkout of this repo with AWESOME_SERVERS_HOME=$PWD/awesome-servers and it federates across the two repos live.

Published snapshot (published/)

published/ holds one directory per npm package, byte-for-byte what the registry serves: 1039 packages, every version matching npm latest.

  • published/INDEX.md is generated from the tree by python3 scripts/index-published.py.
  • scripts/sync-published-snapshot.py re-downloads every package from npm; run it only when every local fix has been published, because it overwrites dist/ from the tarballs.
  • One package carries a licence gate (MCP_LICENSE_KEY): @mrfentmen/vg-resource-mcp. Another 495 still ship tools that answer Not yet implemented; published/INDEX.md lists every one of them.
  • Every package links to this repo (mrfentmen/awesome-servers) as its source.

servers/ holds the older per-server source that predates the snapshot. Where the two disagree, published/ is what users actually install.

来源:README.md,提交 ee04f93

工具

6

latest_cot_report

Latest Commitments of Traders report for a market.

输入参数market必填

cot_history

Recent weekly COT rows for a market.

输入参数limitmarket必填

search_markets

Find futures markets whose name matches a keyword.

输入参数limitquery必填

positioning_extremes

Markets with the most net-long and net-short speculative positioning.

输入参数limit

open_interest_leaders

Futures markets with the largest open interest.

输入参数limit

cot_averages

Average long, short and net positioning over recent weeks.

输入参数weeksmarket必填

版本历史

1
  1. v1.0.2最新Oct 29, 2026

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