{"apiVersion":"v1","directorySlug":"lumenloop-mcp-f5fdfdfbca","title":"Lumen Loop","description":"Stay up to date with the Stellar blockchain ecosystem. News, project directory, events, jobs, and community updates from Lumen Loop.","pageUrl":"https://www.mcpbundles.com/skills/lumenloop-mcp-f5fdfdfbca","connectPath":"importable","connectAction":"import_server","catalogListing":false,"bundleSlug":null,"listingKind":"remote_mcp","kind":"provider","transportUrl":"https://mcp.lumenloop.com/","hostedMcpUrl":null,"toolCount":18,"toolInventoryStatus":"observed","refreshedAt":"2026-11-03T13:26:00.516172+00:00","registryName":"com.lumenloop/lumenloop-mcp-f5fdfdfbca","registryVersion":"2026.11.3","registryEligible":true,"tools":[{"name":"list_documents","description":"Browse/enumerate ONE collection by structured criteria — status, source, date, time period (upcoming/past events) — with sorting and pagination. Its optional \"search\" is the SAME exact case-insensitive SUBSTRING match on title and URL as search_documents (not body text, not meaning). For conceptual or question-phrased discovery, or when you do not know which collection holds the answer, use search_content_semantic instead. The av collection accepts either \"videos\" or \"av\".\nWhen to use: Browse/pa","inputSchema":{"type":"object","$schema":"http://json-schema.org/draft-07/schema#","required":["collection"],"properties":{"wp":{"enum":["all","published","unpublished"],"type":"string"},"page":{"type":"integer","default":1,"minimum":1},"sort":{"type":"string"},"limit":{"type":"integer","default":20,"maximum":100,"minimum":1},"order":{"enum":["ASC","DESC"],"type":"string","default":"DESC"},"period":{"enum":["all","upcoming","past"],"type":"string"},"search":{"type":"string"},"source":{"type":"string"},"status":{"type":"string"},"collection":{"enum":["articles","events","videos","av","jobs","research","proposals"],"type":"string"}},"additionalProperties":false},"annotations":{"readOnlyHint":true,"untrustedContentHint":true},"logicalName":"list_documents","displayName":"list_documents","title":"list_documents"},{"name":"get_document","description":"Get full details of a single document by ID from any collection. The av collection accepts either \"videos\" or \"av\" — they map to the same table.\nWhen to use: Fetch one document by collection + numeric id, after a list/search tool gave you the id.\nReturns: One document. External callers get the summary projection (title, url, summary, long_summary, tags, dates) — full body text and transcripts are not exposed; cite the returned url instead.","inputSchema":{"type":"object","$schema":"http://json-schema.org/draft-07/schema#","required":["collection","id"],"properties":{"id":{"type":"number"},"collection":{"enum":["articles","events","videos","av","jobs","research","proposals"],"type":"string"}},"additionalProperties":false},"annotations":{"readOnlyHint":true,"untrustedContentHint":true},"logicalName":"get_document","displayName":"get_document","title":"get_document"},{"name":"search_documents","description":"Exact keyword lookup: case-insensitive SUBSTRING match on title and URL only (NOT body text, NOT meaning) within ONE collection. Use when you already know wording that appears in a title or URL (e.g. find the article about a known announcement). For conceptual or question-phrased queries use search_content_semantic; to browse a collection by status/date/source use list_documents. The av collection accepts either \"videos\" or \"av\".\nWhen to use: Exact/keyword match on title or URL within one collec","inputSchema":{"type":"object","$schema":"http://json-schema.org/draft-07/schema#","required":["collection","query"],"properties":{"limit":{"type":"number","default":20},"query":{"type":"string"},"collection":{"enum":["articles","events","videos","av","jobs","research","proposals"],"type":"string"}},"additionalProperties":false},"annotations":{"readOnlyHint":true,"untrustedContentHint":true},"logicalName":"search_documents","displayName":"search_documents","title":"search_documents"},{"name":"list_research","description":"List research drafts with optional filters. Used by drafter agents for dedup (\"has anything similar been drafted lately?\") and by agents needing to reference prior work. Returns preview fields only — call get_document(collection=\"research\", id) for full body.\nWhen to use: Browse LumenLoop's own published research/editorial pieces (previews) — id, title, summary, links.\nReturns: Array of research previews: id, title, format, status, summary, created_at — not full bodies.","inputSchema":{"type":"object","$schema":"http://json-schema.org/draft-07/schema#","properties":{"limit":{"type":"number","default":20},"since":{"type":"string"},"format":{"enum":["tweet","thread","long-form","sources","structured"],"type":"string"},"source":{"type":"string"},"status":{"enum":["draft","ai ready","processed","published","failed"],"type":"string"},"editorial_style_slug":{"type":"string"}},"additionalProperties":false},"annotations":{"readOnlyHint":true,"untrustedContentHint":true},"logicalName":"list_research","displayName":"list_research","title":"list_research"},{"name":"search_directory","description":"Search the Stellar ecosystem directory for projects by name, description, or category (substring match). If a multi-word or conceptual query matches no substring, it automatically falls back to semantic project discovery (response carries match_mode: \"semantic\") so you still get the closest projects.\nWhen to use: Start here to find a Stellar ecosystem project by name, keyword, or category when you do not know its slug. Substring match, but a multi-word/conceptual query that hits no substring aut","inputSchema":{"type":"object","$schema":"http://json-schema.org/draft-07/schema#","required":["query"],"properties":{"limit":{"type":"integer","default":20,"maximum":100,"minimum":1},"query":{"type":"string"}},"additionalProperties":false},"annotations":{"readOnlyHint":true,"untrustedContentHint":true},"logicalName":"search_directory","displayName":"search_directory","title":"search_directory"},{"name":"get_project","description":"Get details of a project from the ecosystem directory by slug. Pass compact=true to get a slim writer-friendly shape (~500 chars: slug, title, short description, category, tags, twitter_handles, website, other_names) — recommended for writer agents that just need to verify a slug and read @ handles. Default returns the full row (~8k chars including conflict tracking, source values, field policy).\nWhen to use: Fetch one project BY SLUG. If you only have a name, resolve it to a slug with search_di","inputSchema":{"type":"object","$schema":"http://json-schema.org/draft-07/schema#","required":["slug"],"properties":{"slug":{"type":"string"},"compact":{"type":"boolean","default":false}},"additionalProperties":false},"annotations":{"readOnlyHint":true,"untrustedContentHint":true},"logicalName":"get_project","displayName":"get_project","title":"get_project"},{"name":"get_related_projects","description":"Given a LumenLoop content item (article/av/event/research), return the ecosystem projects it mentions — the 'Mentioned projects' shown on lumenloop.com — with public project info. The source content must be published.\nWhen to use: You have a CONTENT item (article/av/event/research id) and want the ecosystem projects it mentions — the \"Mentioned projects\" on lumenloop.com. The reverse direction (project → content) is find_content_about_project.\nReturns: Array of mentioned projects with public inf","inputSchema":{"type":"object","$schema":"http://json-schema.org/draft-07/schema#","required":["content_id","content_type"],"properties":{"content_id":{"type":"number"},"content_type":{"enum":["article","articles","av","video","videos","event","events","research","proposal","proposals"],"type":"string"}},"additionalProperties":false},"annotations":{"readOnlyHint":true,"untrustedContentHint":true},"logicalName":"get_related_projects","displayName":"get_related_projects","title":"get_related_projects"},{"name":"get_scf_submissions","description":"Get Stellar Community Fund submissions linked to a project, including the full application/proposal text (markdown: sections, milestones, deliverables, budget detail), funding amount, award status, round, and category. Searches by slug or project name — pass at least one.\nWhen to use: Get Stellar Community Fund submissions linked to a specific project. Pass slug (resolve a name via search_directory) or a fuzzy name. For topic-based exploration across all submissions use find_similar_scf_submissi","inputSchema":{"type":"object","$schema":"http://json-schema.org/draft-07/schema#","properties":{"name":{"type":"string"},"slug":{"type":"string"}},"additionalProperties":false},"annotations":{"readOnlyHint":true,"untrustedContentHint":true},"logicalName":"get_scf_submissions","displayName":"get_scf_submissions","title":"get_scf_submissions"},{"name":"get_tags_vocabulary","description":"Get the controlled vocabulary of content tags from the orchestrator. These tags are used for articles and AV content, NOT for directory projects.\nWhen to use: Get the controlled tag vocabulary for CONTENT (articles/AV). For directory project tags use get_project_tags_vocabulary instead.\nReturns: Array of content tag objects (id, name).","inputSchema":{"type":"object","$schema":"http://json-schema.org/draft-07/schema#","properties":{}},"annotations":{"readOnlyHint":true,"untrustedContentHint":true},"logicalName":"get_tags_vocabulary","displayName":"get_tags_vocabulary","title":"get_tags_vocabulary"},{"name":"get_project_tags_vocabulary","description":"Get the controlled vocabulary of project tags. Use these exact tag values when setting directory project tags.\nWhen to use: Get the controlled tag vocabulary for DIRECTORY PROJECTS. For article/AV content tags use get_tags_vocabulary instead.\nReturns: { count, tags: [...] } — each tag: { id, name, slug }.","inputSchema":{"type":"object","$schema":"http://json-schema.org/draft-07/schema#","properties":{}},"annotations":{"readOnlyHint":true,"untrustedContentHint":true},"logicalName":"get_project_tags_vocabulary","displayName":"get_project_tags_vocabulary","title":"get_project_tags_vocabulary"},{"name":"get_categories","description":"Get the controlled vocabulary of categories. Use these exact values when setting project categories.\nWhen to use: Get the exact controlled vocabulary of project categories before filtering or labeling by category. Do not invent category strings.\nReturns: { count, categories: [...] } — each category: { id, name, slug }.","inputSchema":{"type":"object","$schema":"http://json-schema.org/draft-07/schema#","properties":{}},"annotations":{"readOnlyHint":true,"untrustedContentHint":true},"logicalName":"get_categories","displayName":"get_categories","title":"get_categories"},{"name":"get_regions","description":"Get all distinct region values (based_in + operating_region) currently used in the directory\nWhen to use: Get the distinct region values (based_in + operating_region) in use, before filtering projects geographically.\nReturns: { count, regions: [...] } — region name strings.","inputSchema":{"type":"object","$schema":"http://json-schema.org/draft-07/schema#","properties":{}},"annotations":{"readOnlyHint":true,"untrustedContentHint":true},"logicalName":"get_regions","displayName":"get_regions","title":"get_regions"},{"name":"find_content_about_project","description":"Find LumenLoop content (articles, AV, events, research) semantically related to a project — returns LumenLoop's AI-generated summaries + source links (not full text). Cite the returned url.\nWhen to use: All published content related to ONE project, keyed BY SLUG (resolve a name to a slug with search_directory first). For an open-ended topic use search_content_semantic; for entity-name mentions (incl. tokens/orgs) where you only have a name use find_content_by_entity.\nReturns: Content grouped by","inputSchema":{"type":"object","$schema":"http://json-schema.org/draft-07/schema#","required":["slug"],"properties":{"slug":{"type":"string"},"limit":{"type":"integer","default":5,"maximum":100,"minimum":1},"types":{"type":"array","items":{"enum":["articles","av","events","research","proposals","tweets","twitter_accounts","scf_submissions","knowledge"],"type":"string"}},"sources":{"type":"array","items":{"type":"string"}},"date_end":{"type":"string"},"date_field":{"enum":["publishing_date","created_at"],"type":"string"},"date_start":{"type":"string"},"response_format":{"enum":["concise","detailed"],"type":"string","default":"concise"}},"additionalProperties":false},"annotations":{"readOnlyHint":true,"untrustedContentHint":true},"logicalName":"find_content_about_project","displayName":"find_content_about_project","title":"find_content_about_project"},{"name":"search_content_semantic","description":"Meaning-based search across LumenLoop's published content (articles, AV, events, research, SCF submissions) by text query — returns LumenLoop's AI-generated summaries + source links (not full text). Cite the returned url. Supports date/source/type filters. Use this (not search_documents/list_documents) whenever the query is conceptual or phrased as a question, or when you do not know which collection holds the answer; reserve search_documents for exact title/URL keyword lookup.\nWhen to use: Mean","inputSchema":{"type":"object","$schema":"http://json-schema.org/draft-07/schema#","required":["query"],"properties":{"limit":{"type":"integer","default":5,"maximum":100,"minimum":1},"query":{"type":"string","minLength":1},"types":{"type":"array","items":{"enum":["articles","av","events","research","proposals","tweets","twitter_accounts","scf_submissions","knowledge"],"type":"string"}},"sources":{"type":"array","items":{"type":"string"}},"date_end":{"type":"string"},"date_field":{"enum":["publishing_date","created_at"],"type":"string"},"date_start":{"type":"string"},"response_format":{"enum":["concise","detailed"],"type":"string","default":"concise"}},"additionalProperties":false},"annotations":{"readOnlyHint":true,"untrustedContentHint":true},"logicalName":"search_content_semantic","displayName":"search_content_semantic","title":"search_content_semantic"},{"name":"find_similar_projects_semantic","description":"Find projects semantically similar to a given project using embedding cosine similarity. More accurate than tag/category matching.\nWhen to use: Find projects similar to a known project (by slug) via embedding similarity — better than tag/category matching. For keyword search use search_directory.\nReturns: Array of projects ranked by cosine similarity: slug, title, description, similarity score.","inputSchema":{"type":"object","$schema":"http://json-schema.org/draft-07/schema#","required":["slug"],"properties":{"slug":{"type":"string"},"limit":{"type":"integer","default":10,"maximum":100,"minimum":1}},"additionalProperties":false},"annotations":{"readOnlyHint":true,"untrustedContentHint":true},"logicalName":"find_similar_projects_semantic","displayName":"find_similar_projects_semantic","title":"find_similar_projects_semantic"},{"name":"find_similar_scf_submissions","description":"Search SCF (Stellar Community Fund) submissions by embedding similarity. Pass a natural-language query for topic/category discovery or an existing submission slug to find similar prior proposals. Returns title, description, category, round, award_type, the linked_project_slug (the primary directory project, if any), and linked_project_slugs (the full set of directory projects this submission credits).\nWhen to use: Explore SCF submissions by topic (natural-language query) or find proposals simila","inputSchema":{"type":"object","$schema":"http://json-schema.org/draft-07/schema#","properties":{"slug":{"type":"string"},"limit":{"type":"integer","default":15,"maximum":100,"minimum":1},"query":{"type":"string","minLength":1},"round":{"type":"string"},"category":{"type":"string"}},"additionalProperties":false},"annotations":{"readOnlyHint":true,"untrustedContentHint":true},"logicalName":"find_similar_scf_submissions","displayName":"find_similar_scf_submissions","title":"find_similar_scf_submissions"},{"name":"find_av_passages","description":"Find LumenLoop AV (videos/spaces) whose transcripts discuss a topic. Semantic search runs over the transcript, but returns only LumenLoop's AI summary + the recording date (created_at) + an opaque transcript ordering offset (start_offset, NOT playback seconds — do not build timestamp deep-links from it) + link — never transcript text. Cite the returned url.\nWhen to use: Find WHERE in videos/podcasts/spaces a topic is discussed — returns AI summaries of the matching passages plus an opaque orderi","inputSchema":{"type":"object","$schema":"http://json-schema.org/draft-07/schema#","required":["query"],"properties":{"limit":{"type":"integer","default":15,"maximum":100,"minimum":1},"query":{"type":"string","minLength":1},"date_end":{"type":"string"},"date_start":{"type":"string"}},"additionalProperties":false},"annotations":{"readOnlyHint":true,"untrustedContentHint":true},"logicalName":"find_av_passages","displayName":"find_av_passages","title":"find_av_passages"},{"name":"find_content_by_entity","description":"Find LumenLoop content (articles, AV, events, proposals, SCF) that mentions a named ecosystem entity (project / organization / token). Case-insensitive match on the entity name. Returns content metadata + the matched entity; cite the returned url.\nWhen to use: Find content mentioning a NAMED entity (project, organization, token) by case-insensitive name match with LLM-confidence filtering — works even when the entity has no directory slug. If you have a slug, prefer find_content_about_project.\nR","inputSchema":{"type":"object","$schema":"http://json-schema.org/draft-07/schema#","required":["entity"],"properties":{"limit":{"type":"integer","default":30,"maximum":100,"minimum":1},"entity":{"type":"string"},"date_end":{"type":"string"},"date_start":{"type":"string"},"entity_type":{"enum":["project","person","organization","token"],"type":"string"},"content_type":{"enum":["articles","av","events","proposals","scf_submissions"],"type":"string"},"min_confidence":{"type":"number","default":0.5}},"additionalProperties":false},"annotations":{"readOnlyHint":true,"untrustedContentHint":true},"logicalName":"find_content_by_entity","displayName":"find_content_by_entity","title":"find_content_by_entity"}],"toolSource":"directory_preview","agentAction":"both","installLinks":[{"id":"cursor","label":"Cursor","href":"cursor://anysphere.cursor-deeplink/mcp/install?name=Lumen-Loop&config=eyJ1cmwiOiAiaHR0cHM6Ly9tY3AubHVtZW5sb29wLmNvbS8ifQ%3D%3D"},{"id":"vscode","label":"VS Code","href":"vscode:mcp/install?%7B%22name%22%3A%22Lumen-Loop%22%2C%22type%22%3A%22http%22%2C%22url%22%3A%22https%3A%2F%2Fmcp.lumenloop.com%2F%22%7D"},{"id":"vscode-insiders","label":"VS Code Insiders","href":"vscode-insiders:mcp/install?%7B%22name%22%3A%22Lumen-Loop%22%2C%22type%22%3A%22http%22%2C%22url%22%3A%22https%3A%2F%2Fmcp.lumenloop.com%2F%22%7D"},{"id":"claude-web","label":"Claude.ai","href":"https://claude.ai/customize/connectors?modal=add-custom-connector&connectorName=Lumen+Loop&connectorUrl=https%3A%2F%2Fmcp.lumenloop.com%2F"},{"id":"codex","label":"Codex","copyText":"codex mcp add \"Lumen-Loop\" --url \"https://mcp.lumenloop.com/\""},{"id":"chatgpt","label":"ChatGPT","href":"https://www.mcpbundles.com/docs/integrations/chatgpt"}],"catalogUrl":"https://www.mcpbundles.com/api/directory/v1/servers/lumenloop-mcp-f5fdfdfbca","callUrl":"https://www.mcpbundles.com/api/directory/v1/servers/lumenloop-mcp-f5fdfdfbca/tools/{tool}","mcpServerUrl":"https://mcp.lumenloop.com/","liveCatalogUrl":"https://www.mcpbundles.com/api/directory/v1/servers/lumenloop-mcp-f5fdfdfbca?live=1"}