branchly

Name: branchly
Author: io.branchly

MCP serverMCP

Connect your agent to branchly: manage content, prompts, actions, learn from analytics and insights

by io.branchlyhomepage ↗v1.0.0

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Observed by Wellknown

Evidence

Everything here was measured by our prober or read from a registry. Nothing is self-reported.

30-day availability107/108 checks ok

Tools observed via MCP handshake

get_application — Return the full configuration of the authenticated application.
list_nodes — List nodes in the knowledge base. Optionally filter by vertex label(s), data source type(s), or data source IDs. Optionally sort by updated_at ('asc' or 'desc')
create_node — Create a new content node in the knowledge base. Label defaults to 'content'.
read_node — Read a node by its ID. Returns full node details.
update_node — Update a content node by its ID. Only provided fields are updated. Title and text are locale dicts (e.g. {"de": "Titel"}) — provided keys are merged, others pre
list_data_sources — List data sources for the authenticated application. Optionally filter by data source type(s). Returns paginated results ordered by last update.
create_data_source — Create a new data source for the authenticated application. The 'settings' object must match the given 'type'. Returns the created data source. Creating a data
update_data_source — Update a data source by its ID. Only provided fields will be updated (partial update). Returns the updated data source.
run_data_source — Trigger an asynchronous run (sync/crawl) of a data source by its ID. The run is queued as a background job. Returns the accepted status. Track progress with rea
read_data_source_runs — List data source runs for the authenticated application, latest first. Optionally filter by data source ID or run status. Returns the latest runs (default 5) an
list_prompts — List prompts for the authenticated application. Optionally filter by type, subtype, or active status. Returns paginated results ordered by active status then la
create_prompt — Create a new prompt version for the authenticated application. The new prompt is automatically set as active and the previously active prompt of the same type a
update_prompt — Activate or deactivate a prompt by its ID. Use is_active=true to restore a previous prompt version — the currently active prompt of the same type and subtype is
list_tools — List tools configured for the authenticated application. Optionally filter by active status. Returns all matching tools.
read_tool — Read a tool by its ID. Returns full tool details.
create_tool — Create a new tool (AI action) for the authenticated application. Tool names must be unique per application, snake_case, max 64 chars. 'tool_config' and 'functio
update_tool — Update an existing tool by its ID. Fetches the current tool and applies partial updates to name, description, or active status.
read_sessions — List sessions for application. Filter by interaction types (chat, search, navigation, form_submission, voice), embed types, answer types, tool IDs, or a full-te
read_session_detail — Read a single session with its full history in token-dense form. Returns all interactions (chat, navigation, search, form, voice). Document chunks and tool call
get_active_sessions_over_time — Time series of active sessions, bucketed by day or week (auto-chosen from the time window). Each row breaks the total down by interaction type (chat / search /
get_top_locales — Top locales (BCP-47 style, e.g. 'de_DE', 'en_US') across chat, search, and navigation requests, ranked by occurrence count. Use this to understand which languag
get_top_languages — Top detected natural languages of user CHAT questions, ranked by occurrence count. Differs from get_top_locales: locale reflects the embed/browser setting, lang
get_top_devices — Top device categories (e.g. 'desktop', 'mobile', 'tablet') across all request types, ranked by occurrence count. Use this to understand the device mix of real u
get_top_geographies — Top (country, region) combinations across all request types, ranked by occurrence count. Country is an ISO country code; region may be null when unavailable. Us
get_sentiment_distribution — Sentiment distribution of chat answers as counts of 'positive', 'negative', and 'neutral'. Optionally restrict to specific answer types. Use this as a quick qua
get_top_cited_sources — Knowledge-base nodes most frequently cited in chat answers, ranked by citation count. Each row carries the node UUID (vertex_id), its title, optional source URL
get_top_clicked_urls — URLs users actually clicked from inside the embed (search results, citation links, follow-ups, etc.), ranked by click count. Optionally filter by click event ty
get_top_interaction_sources — Page URLs the user was ON when they interacted with the embed (chat, search, navigation, form submission), ranked by occurrence count. Differs from get_top_clic
get_top_searches — Top user search queries (normalized: lowercased, trimmed), ranked by occurrence count. Use this to discover dominant user intents and content gaps; pair with re
get_top_tags — Top tags attached to chat answers (auto-derived classifications), ranked by occurrence count. Optionally restrict to specific answer types. Use this for a quick
get_answer_type_distribution — Distribution of chat answer types (e.g. 'answered', 'no_answer', 'tool_call', 'human_handoff'), ranked by occurrence count. Use this to monitor answer quality:
get_trending_classifications — Time series of trending classifications (topics OR intents inferred from chat content), one series per classification id. Each series item carries a period time
read_chat_request_documents — Read the full document chunks retrieved for a single chat request (QA or SA). Returns chunk_id, vertex_id, title, full text, score, source, data source type, pa
read_chat_request_tool_calls — Read the full tool calls executed for a single chat request. Returns tool_call_id, tool_id, tool_name, tool_type, full arguments (JSON), and full content/respon
read_search_request_results — Read the full search results returned for a single instant-search request. Returns chunk_id, vertex_id, title, full text, and relevance score. Use this to inspe
get_active_sessions_by_embed — Time series of active sessions broken down by embed type (chat, chat_widget, navigator, search_interface, voice, api). Use this to understand which interfaces a
update_chat_request_analytics — Update analytics fields on a chat request: summary, tags, answer_type, sentiment, classification_topic_id, or classification_intent_id. Only provided fields are

when	check	result	http	latency	detail
3 h ago	mcp initialize	ok	200	162 ms	server branchly-mcp-server 0.1.0 · protocol 2025-06-18 · 37 tools
9 h ago	mcp initialize	ok	200	76 ms	server branchly-mcp-server 0.1.0 · protocol 2025-06-18 · 37 tools
15 h ago	mcp initialize	ok	200	70 ms	server branchly-mcp-server 0.1.0 · protocol 2025-06-18 · 37 tools
21 h ago	mcp initialize	ok	200	69 ms	server branchly-mcp-server 0.1.0 · protocol 2025-06-18 · 37 tools
27 h ago	mcp initialize	ok	200	53 ms	server branchly-mcp-server 0.1.0 · protocol 2025-06-18 · 37 tools
34 h ago	mcp initialize	ok	200	66 ms	server branchly-mcp-server 0.1.0 · protocol 2025-06-18 · 37 tools
2 d ago	mcp initialize	ok	200	57 ms	server branchly-mcp-server 0.1.0 · protocol 2025-06-18 · 37 tools
2 d ago	mcp initialize	ok	200	68 ms	server branchly-mcp-server 0.1.0 · protocol 2025-06-18 · 37 tools
2 d ago	mcp initialize	ok	200	81 ms	server branchly-mcp-server 0.1.0 · protocol 2025-06-18 · 37 tools
3 d ago	mcp initialize	ok	200	78 ms	server branchly-mcp-server 0.1.0 · protocol 2025-06-18 · 37 tools

branchly

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