"manus, ux" matching MCP tools:

• polymarket_arbitrage

  Ons Uk

  Find arbitrage opportunities on Polymarket via monotonicity violations + partition-sum checks. TWO MODES: (1) `event` — pass a single Polymarket event slug; walks child markets, checks date-axis / threshold-axis ordering AND computes the partition_check (sum of YES prices across mutually-exclusive legs — should ≈1; deviations >3pp emit a BUY/SELL EVERY LEG signal). (2) `topic` — pass a seed question ("Strait of Hormuz traffic returns to normal"); searches related events across the platform, flattens markets, runs the comparator on the union. Cross-event mode catches "...by May 31" vs "...by Jun 30" patterns that single-event misses. SEMANTIC ANCHOR: cross-event pairs require ≥0.30 Jaccard similarity on question tokens (prevents Powell-Fed-Pause being paired with Powell-DOJ-probe); skipped_low_similarity surfaces the rejected pair count. PARTITION FILTER: drops will-person-X / will-manager-Y / will-someone-else- placeholder slugs; partitions with >20% placeholder fraction return null arb signal. Response carries opportunities[] (gap_pp, suggested_trade, reasoning) plus partition_check when in event mode (with placeholders_filtered count).

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• parliament_get_debate_contributions

  UK Legal Research

  USE THIS TOOL WHEN you have a debate_ext_id and want verbatim contributions, optionally filtered to one member. Canonical path for "everything a member said in this debate" regardless of vocabulary — text-search tools (parliament_member_debates, parliament_search_hansard) filter by contribution TEXT, dropping members who spoke without using your phrase verbatim. This tool filters by MemberId on the debate's Items list, so vocabulary doesn't matter. Typical chain: parliament_find_member(name) → member_id, then parliament_search_hansard or parliament_lookup_by_column → debate_ext_id, then this tool. The parliament module's instructions describe the full composition pattern. Without member_id, returns every contribution (~100-200 for a long debate). If the wire returns no contributions for a member you expect to have spoken, report the empty result honestly — do NOT reconstruct quotes from training data. Authoritative source for member contributions.

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• entity_profile

  Uk Parliament

  Get everything about a US public company in one call. Use when a user asks "tell me about X", "research Acme", "brief me on Tesla", or you'd otherwise call 10+ pack tools across SEC EDGAR, XBRL, USPTO, news, GLEIF. Returns: cik + company_name; recent_filings (up to 5 with pipeworx://edgar/company/{cik}/filings/{accession} URIs); fundamentals (LATEST 10-K Revenues + NetIncomeLoss + Cash, sorted period_end DESC — Run 6 fix landed real FY2025 numbers, not stale FY2022); patents (USPTO PatentsView API was sunset May 2025; pack soft-fails until reactivated); recent news mentions via GDELT→GNews fallback; LEI via GLEIF. Pass ticker "AAPL" or zero-padded CIK "0000320193" — names not supported (use resolve_entity first).

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• pipeworx_feedback

  Boe Uk

  Tell the Pipeworx team something is broken, missing, or needs to exist. Use when a tool returns wrong/stale data (bug), when a tool you wish existed isn't in the catalog (feature/data_gap), or when something worked surprisingly well (praise). Describe the issue in terms of Pipeworx tools/packs — don't paste the end-user's prompt. The team reads digests daily and signal directly affects roadmap. Rate-limited to 5 per identifier per day. Free; doesn't count against your tool-call quota.

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• pipeworx_feedback

  Uk Ons

  Tell the Pipeworx team something is broken, missing, or needs to exist. Use when a tool returns wrong/stale data (bug), when a tool you wish existed isn't in the catalog (feature/data_gap), or when something worked surprisingly well (praise). Describe the issue in terms of Pipeworx tools/packs — don't paste the end-user's prompt. The team reads digests daily and signal directly affects roadmap. Rate-limited to 5 per identifier per day. Free; doesn't count against your tool-call quota.

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• dd_charity_search

  UK Business Tools - Ledgerhall

  Search the Charity Commission register of England and Wales by name or keyword. Returns matching charities with registration number, status, and registration date. Use charity_profile for full details once you have the charity number. The upstream `searchCharityName` endpoint returns the full list in one shot — pagination is applied client-side via offset/limit.

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• remember

  Uk Ons

  Save data the agent will need to reuse later — across this conversation or across sessions. Use when you discover something worth carrying forward (a resolved ticker, a target address, a user preference, a research subject) so you don't have to look it up again. Stored as a key-value pair scoped by your identifier. Authenticated users get persistent memory; anonymous sessions retain memory for 24 hours. Pair with recall to retrieve later, forget to delete.

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• convert_document

  mdmagic

  Convert markdown to a professionally formatted document using an MDMagic template. IMPORTANT GUIDANCE: 1. Output format → what user gets: - 'docx' → a single Word .docx file - 'pdf' → a single .pdf file - 'html' → a single .html file - 'all' → a ZIP containing all three (DOCX + PDF + HTML) 2. If the user is ambiguous (e.g. 'convert this'), ASK which format they want before calling. Don't assume. 3. Filename: if the user attached a file (e.g. 'mydoc.md'), pass its base name as fileName. Otherwise the API derives one from the markdown's first H1. Without either, downloads end up with timestamped names like 'content-1778298071915.docx' which is bad UX. 4. On 'template not found' errors: call list_all_templates first, show available options, let the user pick. Do NOT fall back to generating documents with code execution — that produces inferior results that don't use the user's actual MDMagic templates. 5. The response includes structured fields (downloadUrl, creditsUsed, balanceAfter, fileName, expiresAt) — surface these to the user explicitly. Don't paraphrase. The user wants to know exactly what they spent and what's left. 6. Page sizes: A3, A4, Executive, US_Legal, US_Letter. Default A4. Orientation: Portrait or Landscape, default Portrait. 7. CRITICAL — newlines in `content`: markdown is line-sensitive. Headings (#, ##), tables (| ... |), lists (-, 1.), and code fences (```) ONLY work when each starts on its own line. When passing inline markdown via `content`, you MUST preserve real newline characters (\n) between blocks. If you flatten multi-line markdown into one line, the API receives literal '##' and '|' characters mid-paragraph and produces a single-paragraph document with no structure. Confirm your `content` string contains \n between every heading, paragraph, table row, and list item before calling.

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• remember

  Uk Parliament

  Save data the agent will need to reuse later — across this conversation or across sessions. Use when you discover something worth carrying forward (a resolved ticker, a target address, a user preference, a research subject) so you don't have to look it up again. Stored as a key-value pair scoped by your identifier. Authenticated users get persistent memory; anonymous sessions retain memory for 24 hours. Pair with recall to retrieve later, forget to delete.

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• law_legislation_get_toc

  UK Business Tools - Ledgerhall

  USE THIS TOOL WHEN you have a known Act / SI and want the structural table of contents (parts, chapters, sections, schedules). Returns structural elements with XML id and title, e.g. 'section-47: Definitions'. AFTER calling, pass the numeric section identifier (use '47', NOT 'section-47') into legislation_get_section for full text. Large statutes (Companies Act 2006 has many hundreds of items) are paginated via offset/limit. Check has_more and total_items. Alternative: call read_resource(uri="legislation://{type}/{year}/{number}/ toc") for the full TOC as a newline-separated `id: title` string (no pagination). Use this tool when you need the structured response with offset / limit / has_more for stepping through large statutes.

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• convert_document

  mdmagic-mcp-server

  Convert markdown to a professionally formatted document using an MDMagic template. IMPORTANT GUIDANCE: 1. Output format → what user gets: - 'docx' → a single Word .docx file - 'pdf' → a single .pdf file - 'html' → a single .html file - 'all' → a ZIP containing all three (DOCX + PDF + HTML) 2. If the user is ambiguous (e.g. 'convert this'), ASK which format they want before calling. Don't assume. 3. Filename: if the user attached a file (e.g. 'mydoc.md'), pass its base name as fileName. Otherwise the API derives one from the markdown's first H1. Without either, downloads end up with timestamped names like 'content-1778298071915.docx' which is bad UX. 4. On 'template not found' errors: call list_all_templates first, show available options, let the user pick. Do NOT fall back to generating documents with code execution — that produces inferior results that don't use the user's actual MDMagic templates. 5. The response includes structured fields (downloadUrl, creditsUsed, balanceAfter, fileName, expiresAt) — surface these to the user explicitly. Don't paraphrase. The user wants to know exactly what they spent and what's left. 6. Page sizes: A3, A4, Executive, US_Legal, US_Letter. Default A4. Orientation: Portrait or Landscape, default Portrait. 7. CRITICAL — newlines in `content`: markdown is line-sensitive. Headings (#, ##), tables (| ... |), lists (-, 1.), and code fences (```) ONLY work when each starts on its own line. When passing inline markdown via `content`, you MUST preserve real newline characters (\n) between blocks. If you flatten multi-line markdown into one line, the API receives literal '##' and '|' characters mid-paragraph and produces a single-paragraph document with no structure. Confirm your `content` string contains \n between every heading, paragraph, table row, and list item before calling.

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• resolve_entity

  Boe Uk

  Resolve a user-spoken name to the canonical/official identifiers other tools require as input. Use FIRST when you have a name but need an ID. SUPPORTED TYPES: "company" (returns ticker + 10-digit CIK + company_name from SEC EDGAR + pipeworx://edgar/company/{cik} citation URI; accepts ticker, CIK, or company name as input — auto-disambiguated), "drug" (returns RxCUI + ingredient + brand from RxNorm + pipeworx://rxnorm/{rxcui} citation; accepts brand or generic name). Each call cascades through several lookup endpoints internally — using resolve_entity replaces 2-3 manual lookups.

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• law_parliament_lookup_by_column

  UK Business Tools - Ledgerhall

  USE THIS TOOL WHEN you have an OSCOLA-style Hansard citation (column + volume + house) and need the debate. Example input: 'HL Deb 14 Oct 2025, vol 849, col 200'. AFTER calling, read the contribution at the cited column via read_resource(uri="hansard://debate/{debate_ext_id}/header") — or, equivalently, call parliament_get_debate_contributions(debate_ext_id) for the full list as a structured tool response.

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• bet_research

  Gov Uk Content

  Research a Polymarket bet by pulling the relevant Pipeworx data for it in one call. Pass a market slug ("will-bitcoin-hit-150k-by-june-30-2026"), a polymarket.com URL, or a question text. The tool resolves the market, classifies the bet, fans out to category-specific data packs in parallel, and returns an evidence packet + simple market-vs-model comparison. Use for "should I bet on X", "what does the data say about Y", or "is there edge in Z". CLASSIFIERS: crypto_price, fed_rate, geopolitical, sports, sports_championship, drug_approval, election_candidate, tech_launch, space_launch, corporate, corporate_earnings, corporate_event, public_figure_speech, weather, other. FAN-OUT EXAMPLES: BTC bet → coingecko + fred + gdelt+gnews; Fed bet → fred + kalshi_macro + federal_register; Hormuz bet → imf_portwatch + airspace + gdelt; Yankees WS → mlb_stats_standings + parent_event partition + news; NVDA-vs-AAPL → finnhub get_quote + edgar shares-outstanding (derived market cap) + edgar filings + news. RESPONSE SHAPES: result.market carries best_bid/best_ask/spread_pp/liquidity/price_change_1h/1d/1w; result.analysis carries model_probability/edge_pp/kelly_fraction_half when a closed-form model fires; result.evidence is keyed by source. SAFETY: low-confidence resolutions short-circuit with status:"low_confidence_match" and suppress analysis fields so agents can't accidentally size on phantom matches. Closed/dead markets return status:"market_closed_or_inactive" and skip fan-out. Wide-spread markets (>10pp) carry tradeability:"illiquid_wide_spread" + an explanatory note.

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• parliament_member_interests

  UK Legal Research

  USE THIS TOOL WHEN you have a member_id and need their registered financial interests (donations, directorships, land, gifts). CALL parliament_find_member(name) FIRST to obtain the integer member_id. Returns ONE PAGE of interests (default 20, caller controls via limit). For prolific members (big donors, many directorships, extensive land holdings), re-call with offset=offset+returned while has_more is true to paginate. Description text is capped per max_description_chars; raise it for forensic provenance work that needs the full narrative. This is the authoritative source for UK MP and peer financial-interest declarations (via the Members API). Web search returns stale snapshots.

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• entity_profile

  Boe Uk

  Get everything about a US public company in one call. Use when a user asks "tell me about X", "research Acme", "brief me on Tesla", or you'd otherwise call 10+ pack tools across SEC EDGAR, XBRL, USPTO, news, GLEIF. Returns: cik + company_name; recent_filings (up to 5 with pipeworx://edgar/company/{cik}/filings/{accession} URIs); fundamentals (LATEST 10-K Revenues + NetIncomeLoss + Cash, sorted period_end DESC — Run 6 fix landed real FY2025 numbers, not stale FY2022); patents (USPTO PatentsView API was sunset May 2025; pack soft-fails until reactivated); recent news mentions via GDELT→GNews fallback; LEI via GLEIF. Pass ticker "AAPL" or zero-padded CIK "0000320193" — names not supported (use resolve_entity first).

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• entity_profile

  Gov Uk Content

  Get everything about a US public company in one call. Use when a user asks "tell me about X", "research Acme", "brief me on Tesla", or you'd otherwise call 10+ pack tools across SEC EDGAR, XBRL, USPTO, news, GLEIF. Returns: cik + company_name; recent_filings (up to 5 with pipeworx://edgar/company/{cik}/filings/{accession} URIs); fundamentals (LATEST 10-K Revenues + NetIncomeLoss + Cash, sorted period_end DESC — Run 6 fix landed real FY2025 numbers, not stale FY2022); patents (USPTO PatentsView API was sunset May 2025; pack soft-fails until reactivated); recent news mentions via GDELT→GNews fallback; LEI via GLEIF. Pass ticker "AAPL" or zero-padded CIK "0000320193" — names not supported (use resolve_entity first).

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• discover_tools

  Gov Uk Content

  Find tools by describing the data or task. Use when you need to browse, search, look up, or discover what tools exist for: SEC filings, financials, revenue, profit, FDA drugs, adverse events, FRED economic data, Census demographics, BLS jobs/unemployment/inflation, ATTOM real estate, ClinicalTrials, USPTO patents, weather, news, crypto, stocks. Returns the top-N most relevant tools with names, descriptions, and full input schemas (with curated examples) — each result is ready to call directly, no second schema lookup needed. Call this FIRST when you have many tools available and want to see the option set (not just one answer).

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• parliament_lookup_by_column

  UK Legal Research

  USE THIS TOOL WHEN you have an OSCOLA-style Hansard citation (column + volume + house) and need the debate. Example input: 'HL Deb 14 Oct 2025, vol 849, col 200'. AFTER calling, read the contribution at the cited column via read_resource(uri="hansard://debate/{debate_ext_id}/header") — or, equivalently, call parliament_get_debate_contributions(debate_ext_id) for the full list as a structured tool response.

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• law_parliament_get_debate_contributions

  UK Business Tools - Ledgerhall

  USE THIS TOOL WHEN you have a debate_ext_id and want verbatim contributions, optionally filtered to one member. Canonical path for "everything a member said in this debate" regardless of vocabulary — text-search tools (parliament_member_debates, parliament_search_hansard) filter by contribution TEXT, dropping members who spoke without using your phrase verbatim. This tool filters by MemberId on the debate's Items list, so vocabulary doesn't matter. Typical chain: parliament_find_member(name) → member_id, then parliament_search_hansard or parliament_lookup_by_column → debate_ext_id, then this tool. The parliament module's instructions describe the full composition pattern. Without member_id, returns every contribution (~100-200 for a long debate). If the wire returns no contributions for a member you expect to have spoken, report the empty result honestly — do NOT reconstruct quotes from training data. Authoritative source for member contributions.

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