feat: items 7 + 9 bridge surfaces — 8 cartridges + boj_vector + boj_multimodal

cartridges/chromadb-mcp/cartridge.json

@@ -0,0 +1,22 @@
+{
+  "$schema": "https://boj.dev/schemas/cartridge/v1.json",
+  "spdx": "MPL-2.0",
+  "copyright": "Copyright (c) 2026 Jonathan D.A. Jewell (hyperpolymath) <j.d.a.jewell@open.ac.uk>",
+  "name": "chromadb-mcp",
+  "version": "0.1.0",
+  "description": "Chroma vector DB — embedded (local persistent) or client/server; LLM-app-focused; metadata + document storage alongside vectors.",
+  "domain": "vector",
+  "tier": "Teranga",
+  "protocols": ["MCP", "REST"],
+  "auth": { "method": "optional_bearer", "env_var": "CHROMA_AUTH_TOKEN", "credential_source": "Optional — embedded mode has no auth; client/server may use bearer token." },
+  "api": { "base_url": "local://chromadb-mcp", "content_type": "application/json" },
+  "tools": [
+    { "name": "vector_authenticate", "description": "Store Chroma endpoint URL (or 'embedded' for in-process) + optional bearer.", "inputSchema": { "type": "object", "properties": { "endpoint": { "type": "string" }, "auth_token": { "type": "string" }, "embedding_function": { "type": "string" } }, "required": ["endpoint"] } },
+    { "name": "vector_list_collections", "description": "List collections.", "inputSchema": { "type": "object", "properties": {} } },
+    { "name": "vector_create_collection", "description": "Create a collection with optional embedding function + metadata.", "inputSchema": { "type": "object", "properties": { "name": { "type": "string" }, "metadata": { "type": "object" }, "embedding_function": { "type": "string" } }, "required": ["name"] } },
+    { "name": "vector_delete_collection", "description": "Delete a collection.", "inputSchema": { "type": "object", "properties": { "name": { "type": "string" } }, "required": ["name"] } },
+    { "name": "vector_upsert", "description": "Add documents + vectors + metadata. Chroma computes embeddings if not provided.", "inputSchema": { "type": "object", "properties": { "collection": { "type": "string" }, "ids": { "type": "array" }, "documents": { "type": "array" }, "embeddings": { "type": "array" }, "metadatas": { "type": "array" } }, "required": ["collection", "ids"] } },
+    { "name": "vector_query", "description": "Query by text or embedding with where-filter + document-content filter.", "inputSchema": { "type": "object", "properties": { "collection": { "type": "string" }, "query_texts": { "type": "array" }, "query_embeddings": { "type": "array" }, "n_results": { "type": "integer" }, "where": { "type": "object" }, "where_document": { "type": "object" } }, "required": ["collection"] } },
+    { "name": "vector_delete", "description": "Delete documents by id or where-filter.", "inputSchema": { "type": "object", "properties": { "collection": { "type": "string" }, "ids": { "type": "array" }, "where": { "type": "object" } }, "required": ["collection"] } }
+  ]
+}

cartridges/elevenlabs-mcp/cartridge.json

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+{
+  "$schema": "https://boj.dev/schemas/cartridge/v1.json",
+  "spdx": "MPL-2.0",
+  "copyright": "Copyright (c) 2026 Jonathan D.A. Jewell (hyperpolymath) <j.d.a.jewell@open.ac.uk>",
+  "name": "elevenlabs-mcp",
+  "version": "0.1.0",
+  "description": "Text-to-speech via ElevenLabs API — high-quality voices, multilingual, voice cloning (premium tier), streaming output.",
+  "domain": "multimodal",
+  "tier": "Teranga",
+  "protocols": ["MCP", "REST"],
+  "auth": { "method": "api_key", "env_var": "ELEVENLABS_API_KEY", "credential_source": "ElevenLabs account → Profile → API Keys." },
+  "api": { "base_url": "local://elevenlabs-mcp", "content_type": "application/json" },
+  "tools": [
+    { "name": "audio_authenticate", "description": "Store ElevenLabs API key.", "inputSchema": { "type": "object", "properties": { "api_key": { "type": "string" } }, "required": ["api_key"] } },
+    { "name": "audio_synthesize", "description": "Generate speech from text. Returns audio (mp3 / pcm / opus).", "inputSchema": { "type": "object", "properties": { "text": { "type": "string" }, "voice_id": { "type": "string" }, "model_id": { "type": "string", "enum": ["eleven_multilingual_v2", "eleven_turbo_v2", "eleven_monolingual_v1"] }, "output_format": { "type": "string", "enum": ["mp3_44100_128", "pcm_44100", "opus_48000_128"] }, "stability": { "type": "number" }, "similarity_boost": { "type": "number" } }, "required": ["text", "voice_id"] } },
+    { "name": "audio_list_voices", "description": "List available voices on the account (preset + custom).", "inputSchema": { "type": "object", "properties": {} } },
+    { "name": "audio_clone_voice", "description": "Create a custom voice from sample audio (premium tier only).", "inputSchema": { "type": "object", "properties": { "name": { "type": "string" }, "samples": { "type": "array" }, "description": { "type": "string" } }, "required": ["name", "samples"] } }
+  ]
+}

cartridges/ffmpeg-mcp/cartridge.json

@@ -0,0 +1,21 @@
+{
+  "$schema": "https://boj.dev/schemas/cartridge/v1.json",
+  "spdx": "MPL-2.0",
+  "copyright": "Copyright (c) 2026 Jonathan D.A. Jewell (hyperpolymath) <j.d.a.jewell@open.ac.uk>",
+  "name": "ffmpeg-mcp",
+  "version": "0.1.0",
+  "description": "Local FFmpeg gateway — probe metadata, transcode formats, extract audio, extract frames, concatenate, trim. Glue between whisper / replicate / browser screenshots. Local-only — requires host ffmpeg binary; not Worker-compatible.",
+  "domain": "multimodal",
+  "tier": "Teranga",
+  "protocols": ["MCP", "REST"],
+  "auth": { "method": "none", "env_var": null, "credential_source": "No auth — operates on local files. Sandbox via FFMPEG_ALLOWED_PATHS env if exposing to multi-tenant deployments." },
+  "api": { "base_url": "local://ffmpeg-mcp", "content_type": "application/json" },
+  "tools": [
+    { "name": "media_probe", "description": "Probe metadata (codec, duration, streams, dimensions). Read-only.", "inputSchema": { "type": "object", "properties": { "input": { "type": "string" } }, "required": ["input"] } },
+    { "name": "media_transcode", "description": "Convert between formats with optional bitrate / resolution / codec overrides.", "inputSchema": { "type": "object", "properties": { "input": { "type": "string" }, "output": { "type": "string" }, "video_codec": { "type": "string" }, "audio_codec": { "type": "string" }, "video_bitrate": { "type": "string" }, "resolution": { "type": "string" } }, "required": ["input", "output"] } },
+    { "name": "media_extract_audio", "description": "Extract audio track to its own file (mp3 / wav / opus). Useful as a Whisper input prep step.", "inputSchema": { "type": "object", "properties": { "input": { "type": "string" }, "output": { "type": "string" }, "format": { "type": "string", "enum": ["mp3", "wav", "opus", "aac"] } }, "required": ["input", "output"] } },
+    { "name": "media_extract_frames", "description": "Extract frames at a given interval or specific timestamps. Useful as Replicate vision-model input prep.", "inputSchema": { "type": "object", "properties": { "input": { "type": "string" }, "output_pattern": { "type": "string" }, "fps": { "type": "number" }, "timestamps": { "type": "array" } }, "required": ["input", "output_pattern"] } },
+    { "name": "media_concat", "description": "Concatenate multiple files into one (same codec required, or transcode-then-concat).", "inputSchema": { "type": "object", "properties": { "inputs": { "type": "array" }, "output": { "type": "string" } }, "required": ["inputs", "output"] } },
+    { "name": "media_trim", "description": "Trim/cut to a specific time range.", "inputSchema": { "type": "object", "properties": { "input": { "type": "string" }, "output": { "type": "string" }, "start": { "type": "string" }, "end": { "type": "string" }, "duration": { "type": "string" } }, "required": ["input", "output", "start"] } }
+  ]
+}

cartridges/pinecone-mcp/cartridge.json

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+{
+  "$schema": "https://boj.dev/schemas/cartridge/v1.json",
+  "spdx": "MPL-2.0",
+  "copyright": "Copyright (c) 2026 Jonathan D.A. Jewell (hyperpolymath) <j.d.a.jewell@open.ac.uk>",
+  "name": "pinecone-mcp",
+  "version": "0.1.0",
+  "description": "Pinecone hosted vector DB — serverless indexes, upsert, similarity search, namespaces, metadata filtering.",
+  "domain": "vector",
+  "tier": "Teranga",
+  "protocols": ["MCP", "REST"],
+  "auth": { "method": "api_key", "env_var": "PINECONE_API_KEY", "credential_source": "Pinecone console; environment-scoped." },
+  "api": { "base_url": "local://pinecone-mcp", "content_type": "application/json" },
+  "tools": [
+    { "name": "vector_authenticate", "description": "Store Pinecone API key.", "inputSchema": { "type": "object", "properties": { "api_key": { "type": "string" }, "environment": { "type": "string" } }, "required": ["api_key"] } },
+    { "name": "vector_list_collections", "description": "List indexes (Pinecone calls them indexes).", "inputSchema": { "type": "object", "properties": {} } },
+    { "name": "vector_create_collection", "description": "Create a new index. Pinecone-specific: dimension + metric required.", "inputSchema": { "type": "object", "properties": { "name": { "type": "string" }, "dimension": { "type": "integer" }, "metric": { "type": "string", "enum": ["cosine", "euclidean", "dotproduct"] } }, "required": ["name", "dimension"] } },
+    { "name": "vector_delete_collection", "description": "Delete an index.", "inputSchema": { "type": "object", "properties": { "name": { "type": "string" } }, "required": ["name"] } },
+    { "name": "vector_upsert", "description": "Insert/update vectors with optional metadata + namespace.", "inputSchema": { "type": "object", "properties": { "collection": { "type": "string" }, "vectors": { "type": "array" }, "namespace": { "type": "string" } }, "required": ["collection", "vectors"] } },
+    { "name": "vector_query", "description": "Similarity search. Supports metadata filter + namespace.", "inputSchema": { "type": "object", "properties": { "collection": { "type": "string" }, "query": { "type": "array" }, "top_k": { "type": "integer" }, "namespace": { "type": "string" }, "filter": { "type": "object" } }, "required": ["collection", "query"] } },
+    { "name": "vector_delete", "description": "Delete vectors by id, namespace, or filter.", "inputSchema": { "type": "object", "properties": { "collection": { "type": "string" }, "ids": { "type": "array" }, "namespace": { "type": "string" }, "filter": { "type": "object" } }, "required": ["collection"] } }
+  ]
+}

cartridges/qdrant-mcp/cartridge.json

@@ -0,0 +1,22 @@
+{
+  "$schema": "https://boj.dev/schemas/cartridge/v1.json",
+  "spdx": "MPL-2.0",
+  "copyright": "Copyright (c) 2026 Jonathan D.A. Jewell (hyperpolymath) <j.d.a.jewell@open.ac.uk>",
+  "name": "qdrant-mcp",
+  "version": "0.1.0",
+  "description": "Qdrant vector DB — Rust-native; payloads + filtering; sparse + dense vectors; self-host or Qdrant Cloud.",
+  "domain": "vector",
+  "tier": "Teranga",
+  "protocols": ["MCP", "REST", "gRPC"],
+  "auth": { "method": "api_key", "env_var": "QDRANT_API_KEY", "credential_source": "Qdrant Cloud dashboard or self-hosted bearer." },
+  "api": { "base_url": "local://qdrant-mcp", "content_type": "application/json" },
+  "tools": [
+    { "name": "vector_authenticate", "description": "Store Qdrant URL + API key.", "inputSchema": { "type": "object", "properties": { "url": { "type": "string" }, "api_key": { "type": "string" } }, "required": ["url"] } },
+    { "name": "vector_list_collections", "description": "List collections.", "inputSchema": { "type": "object", "properties": {} } },
+    { "name": "vector_create_collection", "description": "Create a collection. Vector params: size (dim) + distance metric.", "inputSchema": { "type": "object", "properties": { "name": { "type": "string" }, "vector_size": { "type": "integer" }, "distance": { "type": "string", "enum": ["Cosine", "Euclid", "Dot"] } }, "required": ["name", "vector_size"] } },
+    { "name": "vector_delete_collection", "description": "Delete a collection.", "inputSchema": { "type": "object", "properties": { "name": { "type": "string" } }, "required": ["name"] } },
+    { "name": "vector_upsert", "description": "Insert/update points with payload.", "inputSchema": { "type": "object", "properties": { "collection": { "type": "string" }, "points": { "type": "array" } }, "required": ["collection", "points"] } },
+    { "name": "vector_query", "description": "Search by vector with payload filter + score threshold.", "inputSchema": { "type": "object", "properties": { "collection": { "type": "string" }, "vector": { "type": "array" }, "limit": { "type": "integer" }, "filter": { "type": "object" }, "score_threshold": { "type": "number" } }, "required": ["collection", "vector"] } },
+    { "name": "vector_delete", "description": "Delete points by id or filter.", "inputSchema": { "type": "object", "properties": { "collection": { "type": "string" }, "ids": { "type": "array" }, "filter": { "type": "object" } }, "required": ["collection"] } }
+  ]
+}

cartridges/replicate-mcp/cartridge.json

@@ -0,0 +1,20 @@
+{
+  "$schema": "https://boj.dev/schemas/cartridge/v1.json",
+  "spdx": "MPL-2.0",
+  "copyright": "Copyright (c) 2026 Jonathan D.A. Jewell (hyperpolymath) <j.d.a.jewell@open.ac.uk>",
+  "name": "replicate-mcp",
+  "version": "0.1.0",
+  "description": "Replicate hosted ML models — image generation (Stable Diffusion, FLUX), video (Veo, Kling), upscaling, vision (LLaVA), audio (MusicGen). Async prediction model with polling.",
+  "domain": "multimodal",
+  "tier": "Teranga",
+  "protocols": ["MCP", "REST"],
+  "auth": { "method": "api_token", "env_var": "REPLICATE_API_TOKEN", "credential_source": "Replicate account → API tokens." },
+  "api": { "base_url": "local://replicate-mcp", "content_type": "application/json" },
+  "tools": [
+    { "name": "media_authenticate", "description": "Store Replicate API token.", "inputSchema": { "type": "object", "properties": { "api_token": { "type": "string" } }, "required": ["api_token"] } },
+    { "name": "media_run_model", "description": "Run a model by owner/name:version with inputs. Returns prediction_id; poll via media_get_prediction.", "inputSchema": { "type": "object", "properties": { "model": { "type": "string", "description": "Format owner/name or owner/name:version" }, "inputs": { "type": "object" }, "webhook": { "type": "string" } }, "required": ["model", "inputs"] } },
+    { "name": "media_list_models", "description": "Search or list models in the Replicate catalog by collection/owner/name.", "inputSchema": { "type": "object", "properties": { "query": { "type": "string" }, "owner": { "type": "string" }, "collection": { "type": "string" } } } },
+    { "name": "media_get_prediction", "description": "Get status + output of a prediction.", "inputSchema": { "type": "object", "properties": { "prediction_id": { "type": "string" } }, "required": ["prediction_id"] } },
+    { "name": "media_cancel_prediction", "description": "Cancel a running prediction.", "inputSchema": { "type": "object", "properties": { "prediction_id": { "type": "string" } }, "required": ["prediction_id"] } }
+  ]
+}

cartridges/weaviate-mcp/cartridge.json

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+{
+  "$schema": "https://boj.dev/schemas/cartridge/v1.json",
+  "spdx": "MPL-2.0",
+  "copyright": "Copyright (c) 2026 Jonathan D.A. Jewell (hyperpolymath) <j.d.a.jewell@open.ac.uk>",
+  "name": "weaviate-mcp",
+  "version": "0.1.0",
+  "description": "Weaviate vector DB — hybrid (vector + BM25 + filter) search, schema-driven classes, modular vectorisers; self-host or cloud.",
+  "domain": "vector",
+  "tier": "Teranga",
+  "protocols": ["MCP", "REST", "gRPC", "GraphQL"],
+  "auth": { "method": "api_key", "env_var": "WEAVIATE_API_KEY", "credential_source": "Weaviate Cloud Console or self-hosted instance bearer." },
+  "api": { "base_url": "local://weaviate-mcp", "content_type": "application/json" },
+  "tools": [
+    { "name": "vector_authenticate", "description": "Store Weaviate endpoint URL + API key.", "inputSchema": { "type": "object", "properties": { "endpoint": { "type": "string" }, "api_key": { "type": "string" } }, "required": ["endpoint"] } },
+    { "name": "vector_list_collections", "description": "List classes (Weaviate calls collections 'classes').", "inputSchema": { "type": "object", "properties": {} } },
+    { "name": "vector_create_collection", "description": "Create a class with property schema + vectoriser.", "inputSchema": { "type": "object", "properties": { "name": { "type": "string" }, "properties": { "type": "array" }, "vectorizer": { "type": "string" } }, "required": ["name"] } },
+    { "name": "vector_delete_collection", "description": "Delete a class and all its objects.", "inputSchema": { "type": "object", "properties": { "name": { "type": "string" } }, "required": ["name"] } },
+    { "name": "vector_upsert", "description": "Insert/update objects; vectoriser computes embedding if not provided.", "inputSchema": { "type": "object", "properties": { "collection": { "type": "string" }, "objects": { "type": "array" } }, "required": ["collection", "objects"] } },
+    { "name": "vector_query", "description": "Hybrid (vector + BM25 + filter) search. Set alpha to weight vector vs BM25.", "inputSchema": { "type": "object", "properties": { "collection": { "type": "string" }, "query": { "type": "string" }, "vector": { "type": "array" }, "alpha": { "type": "number" }, "limit": { "type": "integer" }, "where": { "type": "object" } }, "required": ["collection"] } },
+    { "name": "vector_delete", "description": "Delete objects by id or where-filter.", "inputSchema": { "type": "object", "properties": { "collection": { "type": "string" }, "ids": { "type": "array" }, "where": { "type": "object" } }, "required": ["collection"] } }
+  ]
+}

cartridges/whisper-mcp/cartridge.json

@@ -0,0 +1,19 @@
+{
+  "$schema": "https://boj.dev/schemas/cartridge/v1.json",
+  "spdx": "MPL-2.0",
+  "copyright": "Copyright (c) 2026 Jonathan D.A. Jewell (hyperpolymath) <j.d.a.jewell@open.ac.uk>",
+  "name": "whisper-mcp",
+  "version": "0.1.0",
+  "description": "Speech-to-text via OpenAI Whisper API + local whisper.cpp fallback. Transcription, language detection, optional translation to English.",
+  "domain": "multimodal",
+  "tier": "Teranga",
+  "protocols": ["MCP", "REST"],
+  "auth": { "method": "optional_api_key", "env_var": "OPENAI_API_KEY", "credential_source": "Required for API backend; local whisper.cpp backend needs no auth." },
+  "api": { "base_url": "local://whisper-mcp", "content_type": "application/json" },
+  "tools": [
+    { "name": "audio_authenticate", "description": "Store OpenAI key (for API backend) or path to whisper.cpp binary (for local).", "inputSchema": { "type": "object", "properties": { "backend": { "type": "string", "enum": ["openai", "local"] }, "api_key": { "type": "string" }, "model_path": { "type": "string" } }, "required": ["backend"] } },
+    { "name": "audio_transcribe", "description": "Transcribe audio file or URL to text. Word-level timestamps optional.", "inputSchema": { "type": "object", "properties": { "source": { "type": "string" }, "language": { "type": "string" }, "timestamps": { "type": "boolean" }, "model": { "type": "string", "enum": ["whisper-1", "tiny", "base", "small", "medium", "large", "large-v3"] } }, "required": ["source"] } },
+    { "name": "audio_detect_language", "description": "Detect spoken language from a short audio sample.", "inputSchema": { "type": "object", "properties": { "source": { "type": "string" } }, "required": ["source"] } },
+    { "name": "audio_translate", "description": "Transcribe and translate any source language to English.", "inputSchema": { "type": "object", "properties": { "source": { "type": "string" }, "model": { "type": "string" } }, "required": ["source"] } }
+  ]
+}