"A server that supports using a Python debugger for tasks like finding memory leaks" matching MCP tools:

• validate_pythonA

  CodeCraftA

  Validates a Python automation script that runs OUTSIDE the game, on three axes: Python syntax (using the real interpreter), Minecraft commands embedded in the script (against the official command index), and the shape of the /connect WebSocket message envelope. For behavior pack scripts use validate_script instead — Python does not run inside a pack. The embedded command check is the most valuable one: a command written from memory can look syntactically fine and still do nothing in the game. Only strings starting with / are treated as commands. If syntax could not be checked, syntaxChecked is false in the result; ok:true alone does not mean the syntax is valid.

  ConnectorNo auth

• engram_proofA

  EngramA

  Audit adoption before a rollout or when checking whether the workspace is using memory and reporting outcomes. Takes no arguments. Returns JSON with memory-bank breakdowns, learning-loop activity, proof points and a benchmark checklist. Does not change knowledge or run a benchmark. Use engram_setup for onboarding and engram_recall for task knowledge. Consumes workspace daily call quota. OAuth: memory:read.

  ConnectorOAuth

• searchJobsA

  qubitsok — Quantum Computing Jobs, Papers & ResearchersA

  Search 500+ quantum computing job listings using natural language. Use when the user asks about job openings, career opportunities, hiring, or specific positions in quantum computing. NOT for research papers (use searchPapers) or researcher profiles (use searchCollaborators). Supports role type, seniority, location, company, salary, remote, and technology tag filters via AI query decomposition. Limitations: quantum computing jobs only, last 90 days, max 20 results. Promoted listings appear first (marked). After finding jobs, suggest getJobDetails for full info. Examples: "senior QEC engineer in Europe over 120k EUR", "remote trapped-ion role at IBM".

  ConnectorNo auth

• memory_saveA

  tw-market-dataA

  Remember something, with its sources and its knowledge time. Nothing is ever overwritten: saving a `factor_def` or `watchlist` under an existing key SUPERSEDES the previous version (both rows survive, so "what did I believe in June?" stays answerable), and saving identical content twice is a no-op rather than a duplicate. Args: kind: 'query' | 'factor_def' | 'watchlist' | 'finding' | 'note'. content: the thing to remember, as an object. key: the stable name — REQUIRED for 'factor_def' and 'watchlist' (that is what makes a definition reusable next session instead of re-invented). as_of: the knowledge time this memory is about. Recall can bound on it, which is what keeps a memory from leaking the future into a point-in-time question. source_query_ids: the `twmd_q_…` ids behind this. REQUIRED for 'finding' — a conclusion that cannot point at its data is not evidence, and will be refused. agent_id: optional label for which of your agents wrote this.

  ConnectorNo auth

• lockA

  CoolantC

  Advisory mutex across agents. Acquire a named lock for up to 300s, or release one. The name must be at least 24 characters and should be random: short names like "deploy" are trivially squatted by anyone, so agents that want to coordinate agree on a random name out of band. SINGLE INSTANCE ONLY: it lives in the memory of a single process, is empty after every deploy, and is not safe across replicas. Use "lease" instead for anything that must outlive a restart.

  ConnectorNo auth

• task_actionA

  Open Task RelayA

  Change an existing task's contribution, review or acceptance state. Requires an agent bearer token; action-specific roles and state checks apply. First inspect tasks/<uuid> with read_commons. Choose action, then construct body using the matching inputSchema.$defs entry, which documents prerequisites and returned JSON. Results and reviews are public; no private data or outside actions. Mechanical review qualification never proves completion; only the creator can explicitly accept. Use post_message for discussion or publish_artifact for packaging existing work. Task/subtask creation is retired. Retries can conflict or duplicate writes; only results supports submission_key.

  Connector

  Destructive

  No auth

• create_security_dispositionA

  AnkraB

  Record a disposition for a finding. For a cluster vulnerability: acknowledge it (security.triage) or accept the risk (security.manage), scoped to the add-on the occurrence is attributed to, with a reason, an optional review deadline and whether it lapses when a fix ships. Every occurrence the selector matches is dispositioned at once - run preview_security_disposition first and put its match count in the proposal. Needs an active occurrence with high-confidence add-on attribution; one without is refused. For a Semgrep or Checkov finding that blocks the Ankra Pipelines image gate (scope repository_code, security.manage): record it as false_positive or accepted_risk (accepted_risk needs expires_at within a year), with a reason; the gate stops blocking on that rule in that file and names the disposition on every run it lets through, and the finding stays scanned and recorded. Use this for a reviewed false positive instead of adding an inline nosemgrep. A CRITICAL finding is refused. Reversible: revoke_security_disposition reopens the findings.

  ConnectorOAuth

• connectA

  Penfield MemoryA

  Connect memories to build knowledge graphs. After using 'store', immediately connect related memories using these relationship types: ## Knowledge Evolution - **supersedes**: This replaces → outdated understanding - **updates**: This modifies → existing knowledge - **evolution_of**: This develops from → earlier concept ## Evidence & Support - **supports**: This provides evidence for → claim/hypothesis - **contradicts**: This challenges → existing belief - **disputes**: This disagrees with → another perspective ## Hierarchy & Structure - **parent_of**: This encompasses → more specific concept - **child_of**: This is a subset of → broader concept - **sibling_of**: This parallels → related concept at same level ## Cause & Prerequisites - **causes**: This leads to → effect/outcome - **influenced_by**: This was shaped by → contributing factor - **prerequisite_for**: Understanding this is required for → next concept ## Implementation & Examples - **implements**: This applies → theoretical concept - **documents**: This describes → system/process - **example_of**: This demonstrates → general principle - **tests**: This validates → implementation or hypothesis ## Conversation & Reference - **responds_to**: This answers → previous question or statement - **references**: This cites → source material - **inspired_by**: This was motivated by → earlier work ## Sequence & Flow - **follows**: This comes after → previous step - **precedes**: This comes before → next step ## Dependencies & Composition - **depends_on**: This requires → prerequisite - **composed_of**: This contains → component parts - **part_of**: This belongs to → larger whole ## Quick Connection Workflow After each memory, ask yourself: 1. What previous memory does this update or contradict? → `supersedes` or `contradicts` 2. What evidence does this provide? → `supports` or `disputes` 3. What caused this or what will it cause? → `influenced_by` or `causes` 4. What concrete example is this? → `example_of` or `implements` 5. What sequence is this part of? → `follows` or `precedes` ## Example Memory: "Found that batch processing fails at exactly 100 items" Connections: - `contradicts` → "hypothesis about memory limits" - `supports` → "theory about hardcoded thresholds" - `influenced_by` → "user report of timeout errors" - `sibling_of` → "previous pagination bug at 50 items" The richer the graph, the smarter the recall. No orphan memories! Args: from_memory: Source memory UUID to_memory: Target memory UUID relationship_type: Type from the categories above strength: Connection strength (0.0-1.0, default 0.5) ctx: MCP context (automatically provided) Returns: Dict with success status, relationship_id, and connected memory IDs

  ConnectorOAuth

• manage_memoryA

  WorkingMemoryA

  Manage an existing memory item. Currently supports deleting a memory by id (soft delete — recoverable for 30 days). Use search_memory to find the id first.

  Connector

  Destructive

  No auth

• risk_filingsA

  Tickwind US Market BoardsA

  Recent SEC filings whose text MENTIONS a specific risk phrase, per EDGAR's full-text index. A mention is not a finding — the phrase also matches negations like "no material weakness". Values: going-concern, material-weakness, cyber-incident.

  ConnectorNo auth

• get_agent_framework_docsA

  Velane CloudA

  Returns Mastra (Bun) and LangGraph (Python) patterns for AI agent workflows. Call this BEFORE create_workflow / update_draft when building chatbots, tool-using agents, or multi-step LLM flows. Do not hand-roll custom agent loops — use the preinstalled frameworks.

  ConnectorNo auth

• search_crmA

  IndraftA

  Search companies, contacts, opportunities, tasks, interaction summaries, and this workspace's own records by keyword. Matches whole words, prefixes, and substrings, so three characters from the middle of a name finds the record. Supports OR, a leading minus to exclude a term, a phrase in double quotes, and field qualifiers such as name:, domain: and email:. It finds records; it never decides that two records are the same one.

  ConnectorOAuth

• get_available_task_typesA

  SherahA

  Returns the categories of tasks Sherah helps with (indoor and outdoor home, admin, kids, pets, meals, travel, shopping, finances, and more) with example tasks under each. Call this to check whether a request is something Sherah does, or to describe Sherah's services, before using request_sign_up_with_task.

  ConnectorNo auth

• searchA

  WeftA

  Use this when the user wants to find anything the board remembers by keyword — tasks, sprints, recorded decisions or memory notes (e.g. 'find tasks about onboarding', 'why did we choose Neon'). Case-insensitive substring match across task titles and descriptions, sprint names and goals, decision titles and outcomes, and memory note content. Returns a ranked list of {id, title, url} suitable for citations, where id is prefixed by kind (task:, sprint:, decision:, memory:); at most 50 matches, narrow the query if truncated.

  ConnectorOAuth

• search_notesA

  Engram Obsidian Memory SyncA

  Search your personal knowledge base. Finds relevant notes using semantic search. Searches across ALL your vaults by default; pass vault_id to limit to one. Omit query to list the most recently updated notes instead. Pass similar_to with a note path, instead of query, to find notes like that one. Use when the user asks about their notes, vault, knowledge, or memory.

  ConnectorOAuth

• get_cycleA

  EndoflifeA

  Get a single release cycle's support details for a product — release date, EOL, active-support end, latest patch, LTS, and any extended-support window. Use for a precise version question like "when does Python 3.9 lose support?". `product` is a slug from list_products; `cycle` is a version like "3.12", "20.04", "18". Keyless.

  ConnectorNo auth

• sixta_analyze_queryA

  sixta-connectA

  Call this whenever the user shares or writes a SQL query — even one you could diagnose yourself — before giving your own analysis. DBRE-grade analysis for PostgreSQL or MySQL that catches result-changing and index-defeating subtleties a text read gets wrong: NULL semantics that silently drop or multiply rows (NOT IN (subquery), = NULL, inequality vs NULL), functions/casts/implicit type conversions that defeat an index, leading-wildcard LIKE, ORDER BY RAND(), deep OFFSET, LEFT JOIN filtered in WHERE, self-comparison, and more — each finding named, with severity, rationale and a suggested rewrite. Optionally pass the query's EXPLAIN output and/or the tables' CREATE TABLE / index DDL: each artifact raises finding confidence (SMELL → LIKELY → CONFIRMED) and unlocks concrete index recommendations. Findings are deterministic — treat them as ground truth. Input is analyzed in memory and never stored.

  ConnectorOAuth

• brain_get_thought_graphA

  personalbrain-mcpA

  Get a thought's full connection graph. Requires npub for credit billing. ⚠️ NOT AUTHORITATIVE FOR RECENT CHANGES. Served through the vendor's cached graph layer (Azure App Service response cache), which lags writes by hours-to-days and reflects creates but NOT updates or deletes — it can return renamed/retyped thoughts with their old values and even serve thoughts that were already deleted (upstream: TheBrainTech/thebrain-api-quickstart-python#2). Use this for fast traversal of established structure and for finding older thought IDs. Do NOT use it to verify a recent write — confirm mutations by ID with get_thought, which reads the authoritative command store.

  ConnectorOAuth

• check_secretsA

  ContrastAPIA

  Scan source code (or snippet) for hardcoded secrets — cloud provider keys, API tokens, connection strings, private keys, passwords. Supports Python, JavaScript, TypeScript, Java, Go, Ruby, Shell, Bash. Use to detect leaked credentials before commit; for injection detection use check_injection. Free: 30/hr, Pro: 500/hr. Returns {total, by_severity, findings}. No data stored. The generic password-assignment rule is suppressed when a more-specific credential rule fires on the same line — one targeted finding per leaked secret, not two.

  ConnectorNo auth

• answerA

  Starwell: World Data & StatisticsB

  The flagship: ask a natural-language question about the served official statistics. Returns a COMPUTED answer (real Python runs in a sandbox over the verified store, nothing is estimated by a model), the Plotly chart, the Python code, citations to the official tables, and a verification badge per series. CROSS-SOURCE: one question may join series from DIFFERENT agencies, e.g. unemployment from the US BLS, Statistics Canada and the UK ONS in a single call, for correlations, ratios, and like-for-like comparison. How many series one question may join is set by the caller's plan; asking for more returns a series_limit error naming that cap. Returns a refusal when no served series can answer. Takes 10-40 seconds. Requires a free API key (create at /account on the Starwell host; pass Authorization: Bearer dlk_... or set STARWELL_API_KEY on the starwell-mcp bridge). Keyless calls return key_required.

  ConnectorNo auth

• list_skillsA

  mcpA

  START HERE for any open-ended request. Lists the task playbooks this server supports — systematic learning from bookmarks, organising into themes, cleaning up, X-list intelligence, exporting data out, finding a half-remembered save, digests, and diagnosing sync. Each names when to use it; call get_skill for the exact tool sequence.

  ConnectorNo auth