C
connor274/syl-guardian-mcp
Guardian checks an agent's causal reasoning before it's allowed to act on it, minimizing wasted spend
在 GitHub 查看 ↗链接已于 2026-11-12 核查 · HTTP 200 · 打开的是厂商自己的官网
安装与配置
取自该仓库的安装命令
pip install syl-guardian-client
解析自我们于 2026-10-29 抓取的该仓库 README;我们未执行过。
这条是仓库自己写的安装方式,不是 MCP 客户端配置,所以不生成 JSON。
配置项的键名以你的客户端为准:客户端与 CLI
- ★ 数取值
- 1 ★ · connor274/syl-guardian-mcp · 取自 GitHub 搜索 API · (2026-11-13 20:00:50 核对)
- 来源明细
- 从该仓库的 GitHub 页面直接读取 · 条目类型:开源项目
- 收录与活跃
- 收录于 2026-10-29 · 最近见到 2026-11-14 · 共见到 17 次 · 被 2 个来源列出
- 评分构成
- 综合分 203 · 1 ★ · 2 个来源 · repo
- 安装
pip install syl-guardian-client
常见问题(答案都来自我们的记录)
怎么安装?
该仓库给出的安装命令是
pip install syl-guardian-client。我们的记录里它是仓库自己提供的;不保证在你的客户端上直接可用。它适合谁 / 用来做什么?
我们把它归在这些标签下: 开源项目。标签来自条目自身,不是我们强加的分类。
谁维护它、还在更新吗?
仓库
connor274/syl-guardian-mcp;我们收录于 2026-10-29;最近见到 2026-11-14。这里没有"官方认证"或"质量评级"——我们只记录来源与时间。# Syl Guardian MCP
以下摘录自该仓库的 README(片段) · 在 GitHub 读完整 README →
Is this ROAS / spend-to-revenue lift actually causal?
Syl Guardian is a Model Context Protocol (MCP) server that works as a causal-validation
agent guardrail. When an AI agent (Claude or any MCP client) is about to act on a claim
about ad spend or budget, such as "this campaign's ROAS is 4x, scale it up" or "ad spend
drove new customers", Guardian checks the claim against your data and returns a pass,
caution or hold verdict, with the naive correlation versus the confounder-adjusted
causal effect, a confidence score and a plain-English recommendation.
Every number is computed deterministically by statistical code and never by an LLM. By
default the summary is a fixed template. For strict reproducibility, set cleaning and
discovery to rule in config: the default (llm) for those two steps can change the
adjustment set, and so the estimate. See Engine config and
Determinism and reproducibility.
This repository holds the public listing metadata and connection instructions for the
hosted Guardian MCP server. Guardian itself is a hosted service.
Endpoint: https://guardian.sylai.io/mcp (streamable HTTP)
Auth: X-API-Key header. Get a trial key at .
Docs:
## Connect
Claude Code:
bash
claude mcp add --transport http syl-guardian https://guardian.sylai.io/mcp \
--header "X-API-Key: "
Claude Desktop (via mcp-remote):
json
"mcpServers": {
"syl-guardian": {
"command": "npx",
"args": ["-y", "mcp-remote", "https://guardian.sylai.io/mcp",
"--header", "X-API-Key:${SYLAPIKEY}"],
"env": { "SYLAPIKEY": " " }
Then ask your agent: "Use guardianreview on this data: did adspend cause
newcustomers? Treat seasonality as a confounder."
Listing the tools does not require a key. A key is checked when guardianreview is called,
and each review counts against your plan or trial quota. Requesting an upload link
(guardianrequestupload) does not count toward quota.
## Use with agents
Add this rule to your agent's instructions so it checks ad-spend and budget claims
before recommending a change:
> Whenever evaluating marketing campaigns, ad platforms, or budget allocation, verify the
> claimed effect is causal using the Syl Guardian MCP tool (guardianreview) before giving
> a final recommendation.
Ready-to-paste sections for CLAUDE.md, AGENTS.md and .cursorrules are in
AGENTRULES.md. Also available:
Rules file:
Machine-readable summary:
Docs:
Trial key:
## Python client
For Python agents and scripts, syl-guardian-client
is a thin, MIT-licensed client for the hosted service. It only makes HTTP calls to
https://guardian.sylai.io; every number is still computed deterministically by the
service, never by an LLM. Set your key in SYLGUARDIANAPIKEY.
bash
pip install syl-guardian-client # extras: [crewai], [langchain]
python
from sylguardianclient import GuardianClient
result = GuardianClient().review(
"adspend", "conversionvalue",
data=rows, timecol="date", step=500,
knownconfounders=["brandqueryclickpct"],
result.verdict # "pass" | "caution" | "hold"
PyPI:
Source:
## Tool: guardianreview
Sanity-checks a causal claim before an agent acts on it.
| Argument | Description |
| cause, effect | Required. Column names for the claim. |
| csv, data or datasetid | Dataset as CSV text, a list of row objects, or the datasetid of a previously uploaded file (see Large datasets). Exactly one. |
Syl Guardian is a Model Context Protocol (MCP) server that works as a causal-validation
agent guardrail. When an AI agent (Claude or any MCP client) is about to act on a claim
about ad spend or budget, such as "this campaign's ROAS is 4x, scale it up" or "ad spend
drove new customers", Guardian checks the claim against your data and returns a pass,
caution or hold verdict, with the naive correlation versus the confounder-adjusted
causal effect, a confidence score and a plain-English recommendation.
Every number is computed deterministically by statistical code and never by an LLM. By
default the summary is a fixed template. For strict reproducibility, set cleaning and
discovery to rule in config: the default (llm) for those two steps can change the
adjustment set, and so the estimate. See Engine config and
Determinism and reproducibility.
This repository holds the public listing metadata and connection instructions for the
hosted Guardian MCP server. Guardian itself is a hosted service.
Endpoint: https://guardian.sylai.io/mcp (streamable HTTP)
Auth: X-API-Key header. Get a trial key at .
Docs:
## Connect
Claude Code:
bash
claude mcp add --transport http syl-guardian https://guardian.sylai.io/mcp \
--header "X-API-Key: "
Claude Desktop (via mcp-remote):
json
"mcpServers": {
"syl-guardian": {
"command": "npx",
"args": ["-y", "mcp-remote", "https://guardian.sylai.io/mcp",
"--header", "X-API-Key:${SYLAPIKEY}"],
"env": { "SYLAPIKEY": " " }
Then ask your agent: "Use guardianreview on this data: did adspend cause
newcustomers? Treat seasonality as a confounder."
Listing the tools does not require a key. A key is checked when guardianreview is called,
and each review counts against your plan or trial quota. Requesting an upload link
(guardianrequestupload) does not count toward quota.
## Use with agents
Add this rule to your agent's instructions so it checks ad-spend and budget claims
before recommending a change:
> Whenever evaluating marketing campaigns, ad platforms, or budget allocation, verify the
> claimed effect is causal using the Syl Guardian MCP tool (guardianreview) before giving
> a final recommendation.
Ready-to-paste sections for CLAUDE.md, AGENTS.md and .cursorrules are in
AGENTRULES.md. Also available:
Rules file:
Machine-readable summary:
Docs:
Trial key:
## Python client
For Python agents and scripts, syl-guardian-client
is a thin, MIT-licensed client for the hosted service. It only makes HTTP calls to
https://guardian.sylai.io; every number is still computed deterministically by the
service, never by an LLM. Set your key in SYLGUARDIANAPIKEY.
bash
pip install syl-guardian-client # extras: [crewai], [langchain]
python
from sylguardianclient import GuardianClient
result = GuardianClient().review(
"adspend", "conversionvalue",
data=rows, timecol="date", step=500,
knownconfounders=["brandqueryclickpct"],
result.verdict # "pass" | "caution" | "hold"
PyPI:
Source:
## Tool: guardianreview
Sanity-checks a causal claim before an agent acts on it.
| Argument | Description |
| cause, effect | Required. Column names for the claim. |
| csv, data or datasetid | Dataset as CSV text, a list of row objects, or the datasetid of a previously uploaded file (see Large datasets). Exactly one. |
收录徽章(可选)
想把收录标记放进 README 就复制这行,可选,不影响收录。
[](https://anclum.com/zh/s/connor274-syl-guardian-mcp/)
- 来源
- github · https://github.com/connor274/syl-guardian-mcp
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