Stay up to date with the Stellar blockchain ecosystem. News, project directory, events, jobs, and community updates from Lumen Loop.
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For AI agents — MCPBundles Directory API
Recommended: Directory API v1 over HTTP for detail and anonymous invoke when eligible (not MCP JSON-RPC on the publisher URL; no user MCPBundles credentials on v1).
GET https://www.mcpbundles.com/api/directory/v1/servers/lumenloop-mcp-f5fdfdfbca
GET https://www.mcpbundles.com/api/directory/v1/servers/lumenloop-mcp-f5fdfdfbca?live=1 (optional live refresh)
GET https://www.mcpbundles.com/api/directory/v1/servers/lumenloop-mcp-f5fdfdfbca/tools/<tool> (one tool: schema + invoke.url)
POST https://www.mcpbundles.com/api/directory/v1/servers/lumenloop-mcp-f5fdfdfbca/tools/{tool}
POST body: flat JSON of tool argument names and values; not an arguments wrapper. Replace {tool} with a tool name from GET detail.
Restricted agent shell (ChatGPT Codex desktop, some IDE sandboxes):
Default command sandboxes often block outbound network. curl exit 6 or "Could not resolve host" for www.mcpbundles.com is usually sandbox DNS — not evidence this site is down.
Retry the same Directory API GET with sandbox_permissions "require_escalated" and a one-sentence justification on the shell tool (Codex on-request approval). Do not tell the user the site is unreachable from sandbox curl alone.
Example justification: Run the public MCPBundles Directory API search outside the command sandbox to complete the user's MCP server lookup.
If the agent has browser access (e.g. Codex @Browser): open https://www.mcpbundles.com/?q=<query> or stay on this page — no shell network needed. Use WebMCP search_mcp_servers then get_mcp_server (document.modelContext / page tools; refresh with fetchTools or getTools if a tool id is missing from the snapshot). Read-only directory search; same index as Directory API v1 GETs. Neither WebMCP nor Directory API v1 uses user MCPBundles credentials.
Without a browser: after escalated curl fails, use GET https://www.mcpbundles.com/?q=<query> with Accept: text/markdown for ranked results.
Hub MCP (connected session): discover_mcp_servers — same filter semantics as search_mcp_servers.
Contract: https://www.mcpbundles.com/agents.md
OpenAPI: https://www.mcpbundles.com/api/directory/v1/openapi.json
Guide: https://www.mcpbundles.com/guides/mcpbundles-directory-api
For MCP client apps (human connect):
MCP connect URL: https://mcp.lumenloop.com/
Skill page: https://www.mcpbundles.com/skills/lumenloop-mcp-f5fdfdfbca
Explore capabilities (18)
read 18
Get
8
Find
5
Search
3
List
2
List Documents
read
list_documents
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".
When to use: Browse/pa
Description may be truncated on the public preview.
List Documents — 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".
When to use: Browse/pa
Get Document — 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.
When to use: Fetch one document by collection + numeric id, after a list/search tool gave you the id.
Returns: 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.
Search Documents — 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".
When to use: Exact/keyword match on title or URL within one collec
List Research — 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.
When to use: Browse LumenLoop's own published research/editorial pieces (previews) — id, title, summary, links.
Returns: Array of research previews: id, title, format, status, summary, created_at — not full bodies.
Search Directory — 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.
When 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
Get your MCP into directories
A working endpoint is step one. Directory coverage is the coordinated launch across ChatGPT, Claude, Cursor, the MCP Registry, and community indexes.
Stay up to date with the Stellar blockchain ecosystem. News, project directory, events, jobs, and community updates from Lumen Loop.
How do I connect Lumen Loop to my AI agent?
Use the MCP endpoint listed on this page in your MCP client configuration. One-click install pills support Claude, Cursor, VS Code, and other hosts. Copy the remote MCP URL if your client needs a manual entry.
How many tools does Lumen Loop provide?
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Get Project — 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).
When to use: Fetch one project BY SLUG. If you only have a name, resolve it to a slug with search_di
Get Related Projects — 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.
When 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.
Returns: Array of mentioned projects with public inf
Get Scf Submissions — 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.
When 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
Get Tags Vocabulary — Get the controlled vocabulary of content tags from the orchestrator. These tags are used for articles and AV content, NOT for directory projects.
When to use: Get the controlled tag vocabulary for CONTENT (articles/AV). For directory project tags use get_project_tags_vocabulary instead.
Returns: Array of content tag objects (id, name).
Get Project Tags Vocabulary — Get the controlled vocabulary of project tags. Use these exact tag values when setting directory project tags.
When to use: Get the controlled tag vocabulary for DIRECTORY PROJECTS. For article/AV content tags use get_tags_vocabulary instead.
Returns: { count, tags: [...] } — each tag: { id, name, slug }.
Get Categories — Get the controlled vocabulary of categories. Use these exact values when setting project categories.
When to use: Get the exact controlled vocabulary of project categories before filtering or labeling by category. Do not invent category strings.
Returns: { count, categories: [...] } — each category: { id, name, slug }.
Get Regions — Get all distinct region values (based_in + operating_region) currently used in the directory
When to use: Get the distinct region values (based_in + operating_region) in use, before filtering projects geographically.
Returns: { count, regions: [...] } — region name strings.
Find Content About Project — 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.
When 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.
Returns: Content grouped by
Search Content Semantic — 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.
When to use: Mean
Find Similar Projects Semantic — Find projects semantically similar to a given project using embedding cosine similarity. More accurate than tag/category matching.
When 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.
Returns: Array of projects ranked by cosine similarity: slug, title, description, similarity score.
Find Similar Scf Submissions — 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).
When to use: Explore SCF submissions by topic (natural-language query) or find proposals simila
Find Av Passages — 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.
When to use: Find WHERE in videos/podcasts/spaces a topic is discussed — returns AI summaries of the matching passages plus an opaque orderi
Find Content By Entity — 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.
When 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.
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