The MCP tool directory.

Produces a pitches overlaid on a strike zone using StatCast data Args: data: (pandas.DataFrame) StatCast pandas.DataFrame of StatCast pitcher data title: (str), default = '' Optional: Title of plot colorby: (str), default = 'pitch_type' Optional: Which category to color the mark with. 'pitch_type', 'pitcher', 'description' or a column within data legend_title: (str), default = based on colorby Optional: Title for the legend annotation: (str), default = 'pitch_type' Optional: What to annotate in the marker. 'pitch_type', 'release_speed', 'effective_speed', 'launch_speed', or something else in the data

Plots a scatter plot with each MLB team Args: data: (pandas.DataFrame) pandas.DataFrame of Fangraphs team data (retrieved through team_batting or team_pitching) x_axis: (str) Stat name to be plotted as the x_axis of the chart y_axis: (str) Stat name to be plotted as the y_axis of the chart title: (str), default = None Optional: Title of the plot

Standalone inbox helper for testing. Create or reuse the saved primary disposable email inbox, then use auth_test_assist first when the task is website auth so you also get reusable cross-site strategy and remembered per-site guidance. Returns email, password, inbox ID, and known-site history for the reusable inbox.

Creates a new function-calling tool in the tenant. Provide name, description, parameters, toolType, and type-specific fields. toolType: External (REST endpoint), Virtual (provider-native like web_search), Agent (sub-agent), CritiqueLoop (producer+critic loop), Mcp (external MCP server). Returns the created tool with its ID.

Appends a new workstream to a content plan. Use after create_content_plan with autoGenerate=false to build a plan manually, or to add a workstream to an existing plan. Workstreams are themed clusters (e.g. 'Authority Building', 'Product Education'). Returns the new workstream ID. Research the cluster (start_deep_research) so articles can be proposed from that research, or feed the ID into add_content_ideas if you already have titles.

Create a new contact record in Clay. This endpoint should only be used when you need to create a completely new contact, not for adding contacts to groups.

Creates a new database as a child page of an existing Notion page.

Create a group or list for the user. If a group with the same name already exists, it will not create a duplicate unless explicitly requested to ignore the check.

Create a note for a contact. Only use this when the user explicitly asks to create, add, or save a note.

Creates a new page as a child of an existing page or database.

List CRM customer data filtered by conversion states with explicit dedupe diagnostics.

Return CRM state statistics (unique deduped customer counts by conversion_state).

CRM read/write operations (no reply generation and no DM sending). Use `action` to select operation; each action has its own required fields. This tool intentionally excludes outbound messaging behaviors. Supported actions: - list_customers - prospect_stats - get_conversation_by_id - update_conversion_state - update_blacklist - get_notes - update_notes

Crops an existing image to a specific rectangle region. Creates a new image — the original is kept. Returns the new image URL. Use get_image_dimensions first if you need to know the source image size.

⚠️ SQL MUST BE VALID IN EVERY DIALECT YOU TARGET — stick to ANSI-ish SELECT syntax when mixing pg/mysql/mssql. `SELECT TOP 10` (mssql) or `LIMIT` (others) will fail on the wrong side. Run the same query across 2-4 connections in parallel; returns per-connection rows + errors for diffing. Canonical use cases: regional compare (`['mssql-reporting-us', 'mssql-reporting-eu']`), cross-dialect sync check (`['prod-postgres-fleet', 'prod-mysql-app']`), 3-env drift, 4-region compare. Resolve every connection name via `list_connections` first; tool fails per-connection on unknown names. ARCHITECT-tier cap: 4 connections; https://www.thinair.co/ for unlimited. [ARCHITECT tier]

Resolve an ISO 4217 currency code such as USD, EUR, or JPY to its name, symbol, decimal places, and which countries use it when you need currency metadata rather than a live exchange rate.

Return the currently authenticated client context for this MCP server session.

大六壬（Da Liu Ren）是中国古代三式之一，以人事预测见长，擅长判断日常生活中的人事问题。 ## 核心概念 - **四课**：由日干、日支加上天地盘推演出的四个课位，反映事物的基本结构 - **三传**：初传（发用）、中传、末传，反映事态发展的过程（起始→发展→结局） - **十二天将**：贵人、腾蛇、朱雀、六合、勾陈、青龙、天空、白虎、太常、玄武、太阴、天后 - **月将**：太阳所在的黄道位置，加于时支之上布天盘 - **课体**：根据四课的推导方式命名（如元首课、重审课、涉害课、遥克课等） - **六亲**：父母、兄弟、子孙、妻财、官鬼——反映事物之间的生克关系 - **神煞**：驿马、桃花、华盖、天德、月德、旬空等辅助判断 ## 解读要点 1. **看课体**：课体决定了取传方法，不同课体暗示事物的性质 - 元首课：事情自上而下，领导之象 - 重审课：需要反复斟酌 - 涉害课：牵涉面广，事多阻碍 - 遥克课：远方来事，需等待 2. **看三传**： - 初传（发用）：事情的起因和开端 - 中传：事情的发展过程 - 末传：事情的最终结局 - 三传递生为吉，递克为凶 3. **看天将**： - 青龙主吉庆、贵人主贵助 - 白虎主凶险、玄武主暗昧 4. **看日干旺衰**：日干代表求测人，旺则有力，衰则无力 5. **看空亡**：旬空之支所临之神/将力量减弱 ## 常见用途 - 求财：看妻财爻、青龙、生门 - 求官：看官鬼爻、朱雀、贵人 - 婚姻：看天后、六合、妻财爻 - 疾病：看天医、白虎、病符 - 出行：看驿马、太冲、天马

FULL data quality + compliance report for a table: per-column stats PLUS a 0-100 health score, type-gated PII detection (email / phone / SSN / etc.), and insight warnings. Slower than `analyze_table` but returns everything needed to audit a table for ownership / compliance / onboarding. Use this when the user says 'profile' or 'quality report' or mentions PII/compliance. [BUILD tier]

Query analytics data for a Minter.io report. Returns CSV data (up to 100 rows). Use accounts_discovery to find report_id and field_discovery for valid tool_name + metric combinations. date_from / to_date: yyyy-mm-dd, defaults to last 30 days. sort / order: for *_detailed tools only.

Get metadata for a specific data.gov.sg collection

Get metadata for a specific data.gov.sg dataset

Initiate download of a data.gov.sg dataset with optional filtering

List all collections on data.gov.sg

List all datasets on data.gov.sg

Check data.gov.sg download status and get download URL

Search for data within a data.gov.sg dataset

Generate a single-use download token for securely downloading datasets.

List and search uploaded datasets with fuzzy matching.

Read, filter, and search dataset rows. Use 'search' to find text across all columns, 'filters' for multi-column AND filtering, or filter_column for simple lookups. For row-level questions ('find rows where X'), use this — not an analysis tool.