"A server for handling vector memory operations" matching MCP tools:

• check_textA

  WSC - Writing Style CheckerA

  Analyze text for writing style issues: weasel words, passive voice, duplicate words, long sentences, nominalizations, hedging, filler adverbs, and research-cited AI tells. Read-only and stateless — text is analyzed in memory on the hosted server and never stored. Returns a plain-text report with each issue's line and column, the matched text, surrounding context, and the reason for AI tells; texts over 100,000 characters return an error message. This hosted server has no filesystem access — the wsc-mcp npm package adds a check_file tool for local files. It only reports issues — to auto-remove duplicate words, follow up with fix_duplicates.

  ConnectorNo auth

• pingA

  Nordic Financial MCPA

  Connectivity check that confirms the Nordic MCP server process is responding. Use this at the start of a session to verify the server is reachable before making other calls. Do not use as a proxy for database health — the server can respond while the Qdrant vector database is temporarily unavailable. To confirm data availability, call search_filings directly. Returns: A greeting string: "Hello {name}! Nordic MCP server is running."

  ConnectorNo auth

• forgetA

  memxusA

  Permanently delete one memory by UUID. When to use: user asks to remove outdated or incorrect context, or to free plan storage. When NOT: fix content → update (mode=replace); find the ID first → list_memories or recall. Requires delete OAuth scope. Non-idempotent: deleting the same memory_id twice fails. Errors: Memory not found, Not authorized to delete this memory. Side effects: removes the memory row and vector embedding with no recovery; invalidates plan cache. The target workspace is always the one the memory itself belongs to (echoed in resolved_workspace); optionally pass workspace: <name> as a safety confirmation — the call fails if the memory is not actually in that workspace.

  Connector

  Destructive

  No auth

• check_textA

  Writing Style CheckerA

  Analyze text for writing style issues: weasel words, passive voice, duplicate words, long sentences, nominalizations, hedging, filler adverbs, and research-cited AI tells. Read-only and stateless — text is analyzed in memory on the hosted server and never stored. Returns a plain-text report with each issue's line and column, the matched text, surrounding context, and the reason for AI tells; texts over 100,000 characters return an error message. This hosted server has no filesystem access — the wsc-mcp npm package adds a check_file tool for local files. It only reports issues — to auto-remove duplicate words, follow up with fix_duplicates.

  ConnectorNo auth

• get_session_usageA

  RoutebaseA

  Return usage metrics for the current MCP session: total tool calls, error count, aggregate duration and response size, per-tool call counts, and session timestamps. Metrics are in-memory and reset when the server restarts or the session goes idle. Use this for what this session has spent; for which toolsets exist at all use list_toolsets.

  ConnectorAPI key

• get_quickstartA

  Vector Panda DocumentationA

  The Vector Panda quickstart: install the veep Python SDK, upload a file, and run similarity queries end to end.

  ConnectorNo auth

• semantic_searchA

  OntonymA

  Search a memory's classes and objects — meaning AND keywords. Two rankers run and their results are fused: a vector leg that matches by meaning (finds the paraphrase) and a keyword leg that matches the literal words (finds the rare token a vector smooths away — an error code, a surname, a part number). Each hit carries `via` saying which legs found it; a hit both agreed on is a stronger answer than one matched on keywords alone. Ties break toward the NEWER row. Because the keyword leg needs no index, search still answers on a memory that was never embedded — with a `note` saying the semantic half was unavailable. `memory` is the slug from list_my_memories. `kind` = 'class' | 'object' | omit. Check `status` and defer on 'unapproved'. `expand=1` inlines each top object hit's FIRST RING — properties plus relationship groups with counts and member previews — so you learn what a hit is and what it touches without a get_object per hit. Prefer expand=1 whenever you intend to follow relationships; for reach beyond one ring, use get_paths instead of hopping get_object calls.

  ConnectorAPI key

• embed_memoryA

  OntonymA

  Build (or top up) the vector index a memory's semantic_search reads. `semantic_search` matches against stored embeddings, so a memory that has never been embedded answers every query with ZERO results — indistinguishable from "nothing matches". Run this once per memory, and again after a large ingestion, to make newly added objects findable by meaning. Idempotent: entities already embedded for the current model are skipped unless `force`. `kinds` defaults to ['object', 'class']. Requires write scope. RETURNS QUICKLY, and usually unfinished. Embedding is CPU-bound, so one call spends a fixed wall-clock budget (~25s) and then reports what is left in `objects_remaining` / `classes_remaining`. It is safe to call again immediately to push it along; you do not have to loop it to zero, because a background worker drains the same backlog on the server.

  ConnectorAPI key

• tower_create_agentA

  OverwingA

  Create a scoped agent identity and its key. Needs an organization key. Scope it to the operations the agent needs (for example create_order) rather than * where you can. The key (ow_agent_...) is returned once, in this result, and this server does not keep it: store it, and send it as the Authorization bearer on a connection used for the agent tools (tower_capabilities, tower_decide, tower_submit_action, tower_get_action, tower_compensate, tower_get_receipt, tower_verify_receipts). Revoke with tower_revoke_agent.

  ConnectorNo auth

• sti_get_platformsA

  Stimulsoft Documentation MCP ServerA

  List every Stimulsoft product/platform that has indexed documentation available through this MCP server. Returns a JSON array of { id, name, description } objects covering the full Stimulsoft Reports & Dashboards product line (Reports.NET, Reports.WPF, Reports.AVALONIA, Reports.WEB for ASP.NET, Reports.BLAZOR, Reports.ANGULAR, Reports.REACT, Reports.JS, Reports.PHP, Reports.JAVA, Reports.PYTHON, Server API, etc.). CALL THIS FIRST when the user's question is ambiguous about which Stimulsoft platform they are using, or when you need to pick a valid `platform` value to pass into `sti_search`. The returned platform `id` values are the exact strings accepted by the `platform` parameter of `sti_search`. This tool is cheap (no OpenAI call, no vector search) — call it freely whenever you are unsure about platform naming.

  ConnectorNo auth

• malware_get_templateA

  website-searchA

  Get Lenny Zeltser's malware analysis report template. The report covers Executive Summary, Sample Snapshot, Malware Family Identification, Component Inventory, Runtime Requirements, Sources, Capabilities, Indicators of Compromise, Analysis Details, What We Don't Know, optional Infection Vector, optional Detection Engineering, About this Report, Appendix: Analysis Environment, and optional Appendix: Analysis Scripts. This server never requests your sample, analysis notes, or indicators and instructs your AI to keep them local—guidelines and the report template flow to your AI for local analysis.

  ConnectorNo auth

• sti_get_platformsA

  docsA

  List every Stimulsoft product/platform that has indexed documentation available through this MCP server. Returns a JSON array of { id, name, description } objects covering the full Stimulsoft Reports & Dashboards product line (Reports.NET, Reports.WPF, Reports.AVALONIA, Reports.WEB for ASP.NET, Reports.BLAZOR, Reports.ANGULAR, Reports.REACT, Reports.JS, Reports.PHP, Reports.JAVA, Reports.PYTHON, Server API, etc.). CALL THIS FIRST when the user's question is ambiguous about which Stimulsoft platform they are using, or when you need to pick a valid `platform` value to pass into `sti_search`. The returned platform `id` values are the exact strings accepted by the `platform` parameter of `sti_search`. This tool is cheap (no OpenAI call, no vector search) — call it freely whenever you are unsure about platform naming.

  ConnectorNo auth

• suggest_refactoringA

  ALM X++ MCP ServerA

  WHEN: developer wants to improve code quality before a PR merge or code review. Triggers: 'refactor', 'clean up', 'simplify', 'too long method', 'nested ifs', 'code smells', 'améliorer le code'. Suggest concrete refactoring actions for YOUR custom D365 F&O X++ code. [!] Only runs on custom/extension code (D365_CUSTOM_MODEL_PATH). Refactoring standard Microsoft code is not actionable. Analyzes: long methods (extract method), deep nesting (guard clauses), row-by-row operations (set-based), large switch statements (strategy pattern), hardcoded strings (constants), unprotected CLR calls (error handling), wide transactions (narrow scope). Returns before/after code examples.

  ConnectorNo auth

• statcan.series.infoA

  apibaseB

  Get metadata for a specific Statistics Canada time-series (vector) by its vector ID. Returns the series title (e.g. "Ontario; Consumer Price Index, All items"), parent table product ID, coordinate within the table, release frequency, decimal precision, and whether the series is terminated. Vector IDs are 8–9 digit numbers assigned by Statistics Canada to uniquely identify each time series. Use series_data to retrieve actual observations. Source: Statistics Canada WDS, Canada Open Licence, no auth required.

  ConnectorNo auth

• get_agent_inbox_handlingA

  mailbox.botB

  Deprecated: use get_inbound_item. Still served unchanged during the alias window. Read /v1/agent-inbox/:id/handling capabilities, version and history. Gated private-mail Live and member-sample Sandbox workflow only; no generated fixtures or managed-PMB fallback. Server chooses source and facility. Handling version is distinct from OCR context_version. Vault is unavailable; physical scans retain the existing owner-confirmed workflow. Required scopes: agent.inbox.read, agent.read. Agent-scoped bearer key required; member/facility keys cannot impersonate an agent. Rollout switches, current member approval, assignment, credential environment and SQL authorization are shared with REST. Never substitute another key or mail API after denial.

  ConnectorNo auth

• error-designA

  Clairvoyance

  Reviews error handling and exception design, applying the "define errors out of existence" principle. Use when reviewing error handling, when a module throws too many exceptions, or when callers must handle errors they shouldn't need to know about. Not for general caller-burden complexity (use pull-complexity-down); this skill is specifically for exception and error-condition strategy.

  ConnectorNo auth

• shippo_list_toolsA

  ShippoA

  List Shippo API operations available through this server. Use this FIRST to discover what operations exist before calling shippo_describe_tool or one of the execute tools. Returns each operation's short name, category, kind (read or write), and one-line description. Filter by `category` (e.g. 'Webhooks', 'Manifests', 'Address Book'), `kind` ('read' or 'write'), or `query` (natural-language keywords matched against names and descriptions). Pass no arguments to list everything. There are ~74 operations spanning 17 categories: Addresses, Address Book, Batches, Carrier Accounts, Customs, Manifests, Orders, Parcels, Pickups, Rates, Refunds, Service Groups, Shipments, Shippo Accounts, Tracking, Transactions, Webhooks.

  ConnectorOAuth

• get_servicesA

  turva-mcpA

  Returns turva.dev's service catalog: the Shopify agent storefront check, agent-readiness audit, advisory, implementation, agent operations, and MCP server design, plus the engagement model and pricing (fixed list prices for the Shopify agent storefront check, audit, advisory and implementation; agent operations and MCP server design on request), and two implementation add-ons that carry a fixed price and are sold only with the diagnosis they follow, bought with it, with its report, or after the report and before implementation starts. Use this when a user asks what turva.dev offers, what it costs, or how an engagement works. For how to reach turva.dev use get_contact instead, and for the rules an engagement follows use get_principles. Read-only: returns static JSON that is compiled into the Worker, so it changes nothing and updates only on deploy.

  ConnectorNo auth

• statusA

  QuotewiseA

  Check server connectivity, authentication status, and database size. When to use: First tool call to verify MCP connection and auth state before collection operations. Examples: - `status()` - check if server is operational, see quote_count, and current auth state

  ConnectorNo auth

• normalize_vectorA

  IA-QA — 130+ QA & Dev Tools for AI AgentsB

  L2-normalize a float vector (produce a unit vector with norm=1). Required by many vector DBs (Pinecone, Qdrant cosine). Supports batch normalization of up to 1000 vectors.

  ConnectorNo auth

• vector_statsA

  IA-QA — 130+ QA & Dev Tools for AI AgentsB

  Compute statistics for a float vector or matrix of vectors: mean, std, L2 norm, min, max, sparsity, top-K indices. Useful for debugging embedding quality and analyzing vector distributions in a vector DB.

  ConnectorNo auth