"Guide to Reading and Writing Data with PostgreSQL" matching MCP tools:

• get_lensA

  mcpA

  Returns a READING LENS: a presentation procedure for this dataset, written for a particular kind of reader. A lens selects which tools to use and frames how their output is presented; it never concludes, never ranks, and carries no write tool — this server has none. Call with no argument to list the lenses. Call with one to get its full procedure: what to lead with, the tools in its scope, and — the part that matters most — what that lens explicitly does not do. Reading a lens before presenting anything from this dataset is the intended use. It is guidance for presentation, not data about the market, and it adds no figures of its own.

  ConnectorNo auth

• create_guidesA

  serpmanticsA

  Create new guides Create one or more new guides based on provided queries. Each guide targets exactly ONE engine and ONE analysis mode, chosen with the optional `source` field (default `google`). How to request each guide type: 1. Google SERP guide (1 credit per guide): omit `source`, or pass `source: "google"`. Example payload: {"queries": ["best crm"], "lang": "en-us"} 1bis. Google AI Overview guide (1 credit per guide). Two modes, like AI engines: `source: "google_ai_overview"` builds the guide from the TEXT of Google's AI answers (AI Overview, completed with AI Mode answers) ; `source: "google_ai_overview_citations"` builds it from the content of the web SOURCES those answers cite (recommended for GEO). Same language/country parameters as a Google SERP guide, 1 credit per guide in both modes. Example payload: {"queries": ["best crm"], "lang": "en-us", "source": "google_ai_overview_citations"} 2. LLM ANSWER guide (4 credits per guide): pass the engine name alone, e.g. `source: "chatgpt"`. The guide is built from the answer text the AI generates for the query. Example payload: {"queries": ["best crm"], "lang": "en-us", "source": "chatgpt"} 3. LLM CITATIONS guide (4 credits per guide) [RECOMMENDED AI mode]: pass the engine name with the `_citations` suffix, e.g. `source: "chatgpt_citations"`. The guide is built from the content of the web pages the AI cites in its answer. Example payload: {"queries": ["best crm"], "lang": "en-us", "source": "chatgpt_citations"} Which AI mode to pick? For GEO (getting a page visible in AI answers), prefer `<engine>_citations`: AI engines send traffic by CITING pages as sources, so the winning move is to look like the pages they cite. The answer-text mode (`<engine>` alone) is mostly useful to analyze how the AI phrases its own answer. When in doubt, pick `<engine>_citations`. The same two modes exist for every AI engine (chatgpt, perplexity, claude, gemini, grok, mistral, deepseek). To optimize the same page for several engines or modes (e.g. Google AND ChatGPT answers AND ChatGPT sources), create one guide per source value on the same query. IMPORTANT, HOW TO READ THE RESPONSE OF THIS ENDPOINT, WHICH SPENDS CREDITS. Queries listed in `guidesFailed` are PROVEN not to have produced a guide and their credit was given back (unless the account has unlimited credits, where nothing was reserved): re-sending them is free and correct. Queries listed in `guidesUnknown` have an UNDECIDABLE outcome and their credit is deliberately KEPT, because the guide was most likely written: DO NOT re-send them, you would pay for the same guide twice. Look them up in `GET /api/v1/guides` after a few minutes instead, and contact support if nothing shows up. Finally, a `200` is NOT a promise that every query produced a guide: compare `guides.length` with the number of queries you sent, never read `success` alone, and never re-send a query just because it is missing from `guides`.

  ConnectorNo auth

• taxonomy_facetsA

  The Chancery Lane ProjectA

  List taxonomy facets and their value slugs across TCLP content. Facets are taxonomy categories like `sector`, `practice_area`, `application`, and `jurisdiction`. Each facet returns the list of slugs that actually appear on the graph, with counts. Use this to discover the vocabulary, then call `taxonomy_content` with chosen slugs. Args: scope: Which labels to include — `clause` (ClauseName only), `guide` (Guide only), or `all` (both, the default). Returns: JSON with "meta" and "facets". Each facet has `name`, `applies_to` (list of Neo4j labels carrying it), and `values` (list of `{slug, count}`, sorted by count desc).

  ConnectorNo auth

• taxonomy_facetsA

  tclp-mcpA

  List taxonomy facets and their value slugs across TCLP content. Facets are taxonomy categories like `sector`, `practice_area`, `application`, and `jurisdiction`. Each facet returns the list of slugs that actually appear on the graph, with counts. Use this to discover the vocabulary, then call `taxonomy_content` with chosen slugs. Args: scope: Which labels to include — `clause` (ClauseName only), `guide` (Guide only), or `all` (both, the default). Returns: JSON with "meta" and "facets". Each facet has `name`, `applies_to` (list of Neo4j labels carrying it), and `values` (list of `{slug, count}`, sorted by count desc).

  ConnectorNo auth

• reading_list_annotateA

  Oxford LedgeA

  WRITE (opt-in): save or update YOUR private note on an Oxford Ledge reading-list entry. One of TWO mutating tools here (the other is ol_paper_trade). DEFAULTS TO A DRY RUN: with _dry_run omitted or true you get a proposal {dry_run: true, tool, args, idempotency_key, message}, not a save. Re-call with _dry_run: false AND that same _idempotency_key to execute; a repeat of the same key returns {replay: true, ...} without writing twice. Requires Plus tier AND an authenticated Oxford Ledge caller -- the local stdio server has no account context and raises AUTH_REQUIRED. `slug` must already exist on /reading-list; `body` is capped at 500 chars. Notes stay PRIVATE; this tool can never publish one. Caveats ride the response's tool_notes.

  ConnectorNo auth

• search_guidesA

  VeteranHQA

  Use this when a veteran asks about a VA topic VeteranHQ has written a guide on. Returns the guides whose text matches the query, highest scoring first, each carrying the guide slug, title, summary and public URL, and no body text. The ordering is lexical and deterministic, computed from where each word of the query appears: a match in the guide title scores above one in the summary, a summary match above one in a section heading, and a heading match above one in the body, with an added score when every word of the query appears somewhere and a further one when the whole query appears in a title. Guides tied on score are ordered by slug, so the same query returns the same list in the same order on every call. No model runs and no network call is made. The limit parameter caps how many guides come back, from 1 to 10, default 5. An empty results array means no guide in this library contains any word of the query, which is a fact about the library and not about VA rules or about what VA holds. Reading one is a second call: pass a returned slug to get_guide. It reads no account data, so the answer is the same for every caller with the same inputs.

  ConnectorNo auth

• get_guideA

  VeteranHQA

  Use this when a slug from search_guides names the guide a veteran needs and the answer should carry what the guide says. Returns the slug, title and summary, the date the facts in it were last verified against its sources, the public URL of the guide on veteranhq.app, the body split into the sections the guide itself defines, each with a heading and its text, and the sources the guide cites, each with a title and a URL. A slug this library does not hold returns a tool error carrying GUIDE_NOT_FOUND, whose message says to call search_guides and use a slug from its results. A guide longer than one result can carry returns the sections that fit, plus omittedSections counting the sections left out and a note stating that count and the guide URL. A single section larger than the whole budget is served shortened at a paragraph or sentence boundary, with truncatedSection naming its heading and the note repeating it, so a section that was cut is distinguishable from one served whole. Those three fields are absent when the whole guide is returned, so a shortened answer is distinguishable from a complete one. A guide states the rules as VeteranHQ read them from the cited sources on the date it reports, and VA decides a claim. It reads no account data, so the answer is the same for every caller with the same inputs.

  ConnectorNo auth

• search_docsA

  pg-aiguideA

  Search documentation with hybrid semantic (vector) and keyword (BM25) search. Use semanticWeight to choose keyword-only (0), semantic-only (1), or a blend; mid values fuse rankings with RRF. Supports Tiger Cloud (TimescaleDB), PostgreSQL, and PostGIS.

  ConnectorNo auth

• water_get_conditionsA

  usgs-water-mcp-serverA

  Get a USGS site's current reading ranked against its full period-of-record daily-mean percentiles for the same calendar day — a "how unusual is this" percentileClass (record-high to record-low), not a flood-stage or drought determination (this tool fetches no authoritative thresholds). The reading is instantaneous but the percentiles are daily-mean, so the ranking is approximate (see historicalContext.comparisonBasis). When the record is too short to rank, returns the reading with historicalContext=null instead of an error. A reading NWIS reports as no data (a seasonal, discontinued, dry, or malfunctioning gage) returns an empty currentValue with the qualifiers naming why, and is not ranked. When the site measures the parameter with several sensors (methods), one reading is used and named by methodId/methodDescription — from the sensor its percentile series is described as when one is, otherwise the most recent across them; water_get_readings lists every method. Use water_find_sites and water_list_parameters to resolve inputs.

  ConnectorNo auth

• find_public_guidesA

  Rung public career guidesA

  Use when someone needs a published Rung occupation, resume-situation, or military-transition guide. Returns public guide facts, source pages, and browser handoffs. Do not use for live jobs, employer search, resume editing, qualification decisions, or private work history; never send personal or resume data.

  ConnectorNo auth

• get_product_visionA

  KeelenA

  Read a project's current product vision (what the product is for). READ THIS BEFORE YOU CALL `set_product_vision`: the setter REPLACES the whole document rather than appending to it, so writing without reading first silently discards whatever the user already recorded. To add a line, read the current text, edit it, and set the full result back. Returns {project_id, product_vision_md, updated_at}. `product_vision_md` is None when no vision has been set. Tenant-scoped: a project not in the caller's workspace 404s.

  ConnectorNo auth

• get_guidesA

  Mamanida Maternity CatalogueA

  Mamanida's editorial buying guides for one storefront, in that storefront's own language. Called without `guide` it lists the published guides (metadata only: title, deck, meta description, pillar, topics, dates and the canonical Mamanida URL), optionally filtered by `topic`. Called with `guide` (the guide slug from the listing) it returns that one localized edition plus its structured body: paragraphs, headings, lists, comparison tables, callouts, links to other guides and category calls-to-action. A `category_cta` gives a `category_slug` you can pass straight to search_products, which is the intended guide → category → product path. Retailer and affiliate URLs are never returned.

  ConnectorNo auth

• get_field_orientationA

  Scholar FeedA

  Returns CANDIDATE FOUNDATIONAL PAPERS for a research topic — cheap retrieval only, no synthesis. Ranks papers by a blend of citation count (0.6 weight, captures importance) and semantic similarity to your topic (0.4 weight). Use this to bootstrap a literature survey or get a fast sense of the landscape. For a synthesized orientation report (key concepts, open problems, reading order), use the /field-guide skill which calls this tool internally. Does not require a Pro API key — no LLM calls are made.

  ConnectorNo auth

• guidesA

  Ownware CatalogueA

  The published guides. With no slug: the list, newest first, each with its title, description, written date and address, optionally only those whose title, description or slug contain every word of q. With a slug: that guide in full, its body as markdown. A guide that is not published is not found.

  ConnectorNo auth

• run_sqlA

  FieldproxyB

  Run ONE read-only PostgreSQL SELECT against the workspace's data and get the rows back (max 500 rows, 5-second limit). Only tables and columns listed by describe_schema are readable. To change data, use propose_write.

  ConnectorAPI key

• get_resortA

  SnowSure — Snow & SkiA

  Single-resort data with a REQUIRED card parameter that picks the interactive UI. card=guide → resort info card (elevation, lifts, season dates). card=photos → photo gallery carousel. card=snow → snow conditions card (score, base depth, forecast). card=full → detailed markdown only, no card. "Resort guide" → card=guide. "Photos/gallery" → card=photos. "Conditions/forecast" / "is it open right now, base depth, lifts open of total" → card=snow (open status, base depth, and lifts open of total). Prefer get_resort_info / get_resort_photos when available (same cards).

  ConnectorNo auth

• reading_timeA

  Moltline Creator StudioA

  Estimate reading and speaking time plus basic content stats. FREE. Typical input {"text": "<your article>"} returns {"words": 1200, "reading_minutes": 5.2, "speaking_minutes": 8.6, "paragraphs": 14, "fit": "newsletter/blog"}. Use when length and pacing are the question. Not for writing quality or grade level (analyze_writing). 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.

  ConnectorNo auth

• reading_timeA

  Moltline Creator StudioA

  Estimate reading and speaking time plus basic content stats. FREE. Typical input {"text": "<your article>"} returns {"words": 1200, "reading_minutes": 5.2, "speaking_minutes": 8.6, "paragraphs": 14, "fit": "newsletter/blog"}. Use when length and pacing are the question. Not for writing quality or grade level (analyze_writing). 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.

  ConnectorNo auth

• update_profileA

  remoetA

  Update the user's Remoet profile core and/or their visibility. Only provide the fields you want to change. Omitted fields are left as-is; pass null to clear a field. Always read the current profile first with get_profile. If the source data (CV, website, etc.) is missing a field, ask the user rather than guessing. Never copy placeholder text like "lorem ipsum". VISIBILITY: pass visibility to control who can see the profile in company candidate lists: NONE (hidden), STARRED (only companies the user has starred, the recommended two-way match), or ALL (every company). Explain the trade-off before changing it. SUMMARY WRITING GUIDE: the summary is the most important field, the first thing companies read. Pattern: [Role] with [X years] experience in [core tech stack]. [One differentiator or achievement]. Example: "Senior Full-Stack Developer with 8 years of experience in React, Node.js, and AWS. Built and scaled a SaaS platform serving 200K users." Under 500 characters. Avoid generic fluff like "passionate developer". Be specific and quantifiable.

  ConnectorNo auth

• update_profileA

  remoet-mcpA

  Update the user's Remoet profile core and/or their visibility. Only provide the fields you want to change. Omitted fields are left as-is; pass null to clear a field. Always read the current profile first with get_profile. If the source data (CV, website, etc.) is missing a field, ask the user rather than guessing. Never copy placeholder text like "lorem ipsum". VISIBILITY: pass visibility to control who can see the profile in company candidate lists: NONE (hidden), STARRED (only companies the user has starred, the recommended two-way match), or ALL (every company). Explain the trade-off before changing it. SUMMARY WRITING GUIDE: the summary is the most important field, the first thing companies read. Pattern: [Role] with [X years] experience in [core tech stack]. [One differentiator or achievement]. Example: "Senior Full-Stack Developer with 8 years of experience in React, Node.js, and AWS. Built and scaled a SaaS platform serving 200K users." Under 500 characters. Avoid generic fluff like "passionate developer". Be specific and quantifiable.

  ConnectorOAuth

• layerz_get_templateA

  LayerzA

  Read a template in full: its blueprint plus its `description` — the markdown usage guide (what it is, how to use it, which business rules to fill). The guide IS the underlying model's FINANCE.md (a template's id equals its model id): to edit a template's guide, edit that model's FINANCE.md via layerz_set_finance_md — it propagates live, not as a snapshot. After forking or applying a template, follow the guide and update the new model's FINANCE.md so the conventions and objective match the project. Account-level, read-only.

  ConnectorOAuth