"A search for the characters '{"'" matching MCP tools:

• parliament_member_debates

  UK Legal Research

  USE THIS TOOL WHEN you have a member_id and want contributions where THAT member used a specific topic phrase verbatim (text-body search). CALL parliament_find_member(name) FIRST to obtain the integer member_id. This is a name-based text-body search — it matches contributions whose TEXT contains the topic phrase. A member who spoke in a debate but didn't use your phrase verbatim is filtered out. For verbatim retrieval of every contribution by a member in a known debate (regardless of vocabulary), use parliament_get_debate_contributions(debate_ext_id, member_id=...) instead. Each contribution's text field is capped at 3000 characters.

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• law_parliament_member_debates

  UK Business Tools - Ledgerhall

  USE THIS TOOL WHEN you have a member_id and want contributions where THAT member used a specific topic phrase verbatim (text-body search). CALL parliament_find_member(name) FIRST to obtain the integer member_id. This is a name-based text-body search — it matches contributions whose TEXT contains the topic phrase. A member who spoke in a debate but didn't use your phrase verbatim is filtered out. For verbatim retrieval of every contribution by a member in a known debate (regardless of vocabulary), use parliament_get_debate_contributions(debate_ext_id, member_id=...) instead. Each contribution's text field is capped at 3000 characters.

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• search

  Sofya

  Search the web for current information on any topic. Returns extracted page content, not just snippets. Best for factual lookups, specific questions, or when you need a list of sources. For open-ended questions that need synthesis across many sources, use the research tool instead. For news queries (current events, breaking news, politics, world events), set topic="news" to search news sources specifically. This returns recent articles with publication dates. Set include_answer=true to get an AI-synthesized answer alongside results (adds 10 credits). This is the sweet spot for most agent tasks, e.g. basic + include_answer = 12 credits, much cheaper than a full 50-credit research call. Returns: query, answer (if requested), results (array of {title, url, content, description, fetched, published_date}), search_depth, topic, elapsed_ms, credits_used, credits_remaining, altered_query. Args: query: The search query search_depth: "basic" (default) for extracted page content (2 credits), "snippets" for SERP snippets only without page fetching (1 credit) max_results: Number of results (default 10, max 20) include_answer: Generate an AI answer that synthesizes the search results (adds 10 credits) include_domains: Only include results from these domains (max 10) exclude_domains: Exclude results from these domains (max 10) topic: "general" for web search, "news" for news articles. use "news" for current events, breaking news, politics, or any time-sensitive query freshness: Filter by recency - "day", "week", "month", "year", or "YYYY-MM-DD:YYYY-MM-DD"

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• search

  DC Member API

  GET /search — Cross-resource omni-search Cross-resource search across profiles, rooms, messages (incl. private DMs + group DMs you're in), events, and chapters in one round trip. Returns the top-N matches per resource, grouped by resource. Use this when you don't yet know which resource carries the answer — agents typically call this first, then drill into a specific `GET /search/<resource>` for more depth on a single bucket. There's no page param: when you hit the per-resource limit and want more, switch to the per-resource endpoint for that one. The events slice has a baked-in forward-looking default (events ending in the last 30 days or later, and currently enabled) — this matches the in-app "Search across DC" surface. Use `GET /search/events` directly to look further back in time. **Query syntax (`q=`):** plain words match with prefix + typo tolerance. Wrap a phrase in double quotes to require an exact ordered match — e.g. `q="remote work"`. AND/OR/NOT/parentheses are NOT parsed in `q=` — use the structured filter params below for boolean composition.

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• slugify

  mcp

  Use this when you need a URL- or filename-safe slug from arbitrary text. Deterministic: same input, same output. Applies Unicode NFKD normalization, strips combining accents, and transliterates non-decomposing letters (ß->ss, æ->ae, œ->oe, ø->o, đ->d, ł->l, þ->th, ð->d, plus uppercase variants), then collapses every run of non-alphanumeric characters to a single separator and trims separators; e.g. "Héllo Wörld!" -> "hello-world". Emoji, CJK, and any other characters with no ASCII form are dropped. Prefer this over transliterating Unicode yourself, which models routinely get wrong. Returns { error } when no URL-safe characters remain.

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• leave_feedback

  AgentMarketplace

  Leave feedback about AgentMarketplace itself — bugs, confusing tools, feature requests. This is for feedback about the platform, not about a counterparty. There is no reputation or rating system here — that lives in AgentTrust. Args: access_token: AgentAuth bearer token (requires ``market.read``). message: Free-text feedback, up to 2000 characters. Returns: ``{"recorded": true}`` on success.

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• twprojects-search

  mcp

  Cross-entity keyword search across projects, tasks, messages, comments, users and more; restrict which entity types are searched with types. Long content fields in the sideloaded records are truncated at 500 characters and marked where they are cut; the marker names the tool that returns the full record. Completed items are excluded unless include_completed_items is true, so an empty result may mean the matching work is already done rather than missing.

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• search

  TunnelMind Data API

  Searches both the domains table and the entities table simultaneously. Returns matching domains (by domain name) and entities (by name or slug) in a single response. Minimum 2 characters, maximum 100 characters. Use this tool when: - You have a partial name and need to identify what tracker or entity it belongs to. - You want to find all TunnelMind records related to a company name like "Google" or "Oracle". - You are resolving an ambiguous domain (e.g., does `criteo.com` appear in the tracker DB?). Do NOT use this tool when: - You know the exact domain — use `get_domain` instead (faster, more complete). - You know the exact entity slug — use `get_entity` instead. - You want to browse by category or industry — use `list_domains` or `list_entities`. Inputs: - `q` (query, required): Search string, 2-100 characters. Matched against domain names and entity names/slugs. Returns: - `domains`: array of matching domain records (list item format). - `entities`: array of matching entity records (list item format). - Both arrays may be empty if no matches found. No pagination — results are capped at 20 per type. Cost: - Free tier: included in 50 req/day. Pro/enterprise: included in plan. Latency: - Typical: <200ms, p99: <500ms.

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• search_builders

  BuilderVet — NSW builder licence & risk history

  Search Australian (currently NSW) builders, contractors and building companies by name; optionally filter by postcode. Returns matching entities with their licence status and a slug to pass to get_builder_risk / get_builder_timeline. Example: query='Acme Building' → '- Acme Building Pty Ltd (Current), 2099 → slug: acme-building-pty-ltd-1a2b'. Names are matched loosely, so try the trading name AND the legal (Pty Ltd) name if the first search misses. Query must be at least 2 characters.

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• search

  UseMyContext.ai

  Search the user's files by filename and return matching documents in the deep-research result shape. ALIAS: this is the SAME search as search_files (same data, same permissions) - use it when your client requires the id/title/url search contract (ChatGPT deep research); otherwise prefer search_files for richer file metadata. Each result's id can be passed to fetch (or get_file) to read that document. Read-only; always allowed.

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• goal-dismiss-red-team

  Planner — provable "done" for AI agents

  Dismiss the red-team finding that blocks a goal from starting, when you disagree with the verdict. Requires a reason of at least 80 characters explaining why the counterexample does not apply. The dismissal is recorded in goal history and surfaced in goal-get, so "agent overrode the gate" stays distinguishable from "no hole was found". Prefer fixing the acceptance criteria via goal-add-criterion — dismissing leaves the hole open.

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• search

  MedRates

  Search for medical procedure prices by code or description. Use this for direct lookups when you know a CPT/HCPCS code (e.g. "70551") or want to search by keyword (e.g. "MRI", "knee replacement"). For code-like queries → exact match on procedure code. For text queries → searches code, description, and code_type fields. Supports filtering by insurance payer, clinical setting, and location (via zip code or lat/lng coordinates with a radius). NOTE: Results are from US HOSPITALS only — not non-US providers, independent imaging centers, ambulatory surgery centers (ASCs), or other freestanding facilities. Args: query: CPT/HCPCS code (e.g. "70551") or text search (e.g. "MRI brain"). Must be at least 2 characters. code_type: Filter by code type: "CPT", "HCPCS", "MS-DRG", "RC", etc. hospital_id: Filter to a specific hospital (use the hospitals tool to find IDs). payer_name: Filter by insurance payer name (e.g. "Blue Cross", "Aetna"). plan_name: Filter by plan name (e.g. "PPO", "HMO"). setting: Filter by clinical setting: "inpatient" or "outpatient". zip_code: US zip code for geographic filtering (alternative to lat/lng). lat: Latitude for geographic filtering (use with lng and radius_miles). lng: Longitude for geographic filtering (use with lat and radius_miles). radius_miles: Search radius in miles from the zip code or lat/lng location. page: Page number (default 1). page_size: Results per page (default 25, max 100). Returns: JSON with matching charge items including procedure codes, descriptions, gross charges, cash prices, and negotiated rate ranges per hospital. Only high-confidence results (with at least one usable price) are included. Each result includes last_updated (ISO date of the per-hospital MRF ingest) and mrf_date (ISO date the hospital self-reported in the MRF file). When all results are filtered out, filtered_low_confidence=true is set so the agent can say "no high-confidence prices found" rather than asserting that no prices exist.

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• search

  search

  Search the web via Aimnis. Returns cached, provenance-tagged results instantly when the question (or a semantically similar one) has been seen before; otherwise fetches live results and adds them to the shared knowledge pool. Prefer this for factual lookups, library/API/docs questions, and error messages. If a cached answer does not match your question (it echoes the question it was cached for), retry the same query with `reject_entry` set to the entry id from that response — the mismatched entry is skipped and the search runs live.

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• emem_memory_token

  emem, the verifiable memory protocol for the physical world

  Mint a citation handle, `emem:fact:<cell64>:<fact_cid>` (or `:<state_cid>`), that any agent or LLM resolves to the byte-identical signed object. The antidote to referential drift on the value side: hand this one string to another agent instead of re-describing the fact. Validates both components are non-empty and free of the `:` separator. Memory algebra: the `cite` operation (https://emem.dev/docs/model.html). When to use: Call when the agent wants a single rebindable string to cite a place plus an attested fact across messages, threads, agents, or tools, without re-fetching or re-describing it. Pair with `emem_verify_receipt` on the receiving end to check the signed payload. To cite an OBJECT rather than a single reading, use emem_entity's `emem:entity:` token. FOR MANY FACTS, USE emem_memory_bundle INSTEAD, and this is a measured cost rather than a style preference. Measured over 131 scalar facts at 12 places across 57 bands: a token is 84 characters and 51 LLM tokens, while the signed value it points at averages 10.9 characters and 5.4 LLM tokens. So N individual tokens cost roughly 9.5x the CONTEXT of simply pasting the N numbers (7.7x by characters; the gap is BPE fragmenting a base32 cid, and LLM tokens are the unit that bills a window), and an N-token prompt hits the context wall SOONER than the plain values would. A bundle is 38 characters and 23 LLM tokens at ANY N up to 256 and resolves in one round trip: it beats individual tokens from N=1 and beats pasting the plain values from N>=5. Individual tokens are for citing ONE fact you must be able to verify later; they are the wrong tool for carrying a set. Example arguments: {"cell":"defi.zb493.xoso.zcb6a","fact_cid":"cxjiu7l54ujzrpnekp24n4534yojpue4mprddbvevnqtti3lh5bq"}

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• search

  The Chancery Lane Project

  Search the TCLP knowledge graph using fusion search (semantic + BM25). Args: query: Free-text search query (max 1000 characters). node_type: Content scope — "tclp" (clauses, glossary terms, guides), "lrsf" (laws, regulations, standards, frameworks), or "all". limit: Maximum number of results to return (1–50). rerank: Whether to apply RRF reranking when combining graph and text results. include_full_text: Include each hit's full body text (Markdown). Off by default — bodies are large; request only when you need the content, and prefer a small `limit` when you do. Returns: JSON with "meta" (totals, timing) and "results" (ranked hits with title, url, content_type, scores, and optionally relationships and full_text).

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• search

  tclp-mcp

  Search the TCLP knowledge graph using fusion search (semantic + BM25). Args: query: Free-text search query (max 1000 characters). node_type: Content scope — "tclp" (clauses, glossary terms, guides), "lrsf" (laws, regulations, standards, frameworks), or "all". limit: Maximum number of results to return (1–50). rerank: Whether to apply RRF reranking when combining graph and text results. include_full_text: Include each hit's full body text (Markdown). Off by default — bodies are large; request only when you need the content, and prefer a small `limit` when you do. Returns: JSON with "meta" (totals, timing) and "results" (ranked hits with title, url, content_type, scores, and optionally relationships and full_text).

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• generate_character_turn

  spriteship

  PAID (~400 credits — ONE 2-second rotation video). Spins the character through a full 360 so the sprite exists from every side; its frames are also what the directional-pose extractor reads, which is what makes top-down characters usable in more than one facing (isometric projects use top-down characters). ONLY topdown and isometric characters are supported — any other game type errors 400 TURN_NOT_SUPPORTED (topdown_overhead: the engine rotates the sprite image; platformer/point_and_click: side/front views, mirror instead). Eligibility reads the STORED CHARACTER gameType, not its project: a topdown character inside a platformer project is supported. This explicit visible turn is separate from the internal mid-walk rotation that generate_character_animation may plan for eligible directional walk/run clips; do not call it as mandatory setup for every animation. Lands as the animation "turn", or "turn_<seedPoseId>" when seeded from a pose. An existing turn is NEVER replaced: an occupied name becomes turn_2, turn_3, and so on. It 409s (ENTITY_BUSY) while ANY other job is running on the character, because it rebuilds the spritesheet: poll that job first. Returns { jobId, animation } — poll get_job. A successful 360 pauses at waiting_approval with directionalPoseReview; present all eight previews and call approve_directional_poses before treating the job as complete. DEFAULTS TO A COST PREVIEW — see the dryRun argument.

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• search_products

  SendaMeal Storefront

  Search products by a term Arguments: term - the search term to look for products. It should be at least 3 characters long. cursor - optional, used for pagination. If provided, it will return the next page of results after. Pagination: Supports pagination with 'cursor' arguments. If 'cursor' is not provided, it will return the first page of results. Value for 'cursor' can be obtained from the 'nextCursor' field in the response. If 'nextCursor' is null, it means there are no more results to fetch. If value of cursor is null (or a string representation of 'null') dont send it in the payload. Results: Each product includes 'requiresFileUpload'. When true, the product has a required file-upload option (e.g. "upload your design") and shouldn't be added to cart through this assistant. Do not attempt to purchase it — tell the user it must be ordered on the website. Flow: - Call this tool with a 'term' argument and optionally with 'cursor' to search for products. - if you find a matching product, call 'get_product_details' with the product ID to get its variants and options (if any). - if 'requiresFileUpload' is true, inform the user the product needs a file upload and cannot be purchased here. - Call 'add_item_to_cart' with results of 'search_products' and 'get_product_details' (variant) tools to add the product to the cart. - [IMPORTANT] If product has variants ask user to pick

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• list_hexagrams

  I Ching Hexagram MCP

  Compact index of all 64 I Ching hexagrams (id, name, pinyin, characters, essence, trigrams, url). Optional order: kingwen (default), mawangdui, eightpalaces, binary. This is the summary index only; get_hexagram (or get_hexagrams) returns full detail for a known number, get_all_hexagrams returns the full dataset in one call, and search_hexagrams finds hexagrams by text. Data © IChing.Rocks — attribution is a condition of the license terms: https://iching.rocks/mcp-terms.

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• search

  Whatic IC Datasheets

  Search the datasheet corpus; returns hit records (metadata + snippet, each with an opaque `ref`). Pass a ref list to `get_segments` for full content. If you already know the part number(s), prefer `lookup` — it fuses this search with `get_segments` in one call and groups full content per part. Use `search` when the part is unknown, or to triage snippets before pulling full content. For part-specific queries, pass scope='device:<MPN>' (e.g. scope='device:NE5532') to restrict hits to that part and avoid cross-part contamination.

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