ZeroDB MCP Server vs Anydb MCP
A side-by-side look at the ZeroDB MCP Server and Anydb MCP MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.
Verdict: choose ZeroDB MCP Server for databases work as a local process; choose Anydb MCP for databases as a local process. You can also run both side by side in one mcpServers block.
Which MCP server should you choose?
Choose ZeroDB MCP Server when
- You need dedicated capabilities in the Databases domain.
- You prefer a local stdio subprocess transport.
- You have the keys it needs:
ZERODB_API_URL, ZERODB_PROJECT_ID, ZERODB_API_KEY. - You want tools like
zerodb_generate_embeddings, zerodb_embed_and_store, zerodb_semantic_search.
Choose Anydb MCP when
- You need dedicated capabilities in the Databases domain.
- You prefer a local stdio subprocess transport.
- You want tools like
db_list, db_query, db_schema.
Feature & specification comparison
Rows where the two servers differ are marked.
| Spec | ||
|---|---|---|
| Category | Databases | Databases |
| Quality signal | 63/100 · Good | 65/100 · Great |
| Install command | Confirmed | Confirmed |
| Transport | Local subprocess (stdio) | Local subprocess (stdio) |
| Auth | Not declared | Not declared |
| Pricing | Not declared | Free |
| Required env vars | ZERODB_API_URLZERODB_PROJECT_IDZERODB_API_KEY | None listed |
| Verified owner | Community listing | Community listing |
| GitHub stars | 0 | 1 |
| Directory activity | 1 views 0 installs 0 upvotes | 5 views 0 installs 0 upvotes |
| Tools | 85 | 5 |
| Full listing | View ZeroDB MCP Server | View Anydb MCP |
Tools & capabilities
ZeroDB MCP Server tools 85
zerodb_generate_embeddingsGenerate embeddings using specified model (384/768/1024 dimensions). Supports BAAI/bge-small-en-v1.5 (384-dim, default), BAAI/bge-base-en-v1.5 (768-dim), BAAI/bge-large-en-v1.5 (1024-dim). Use when you need raw embedding vectors without storing them. Does not persist data — for embed + store in one step, use zerodb_embed_and_store instead.zerodb_embed_and_storeGenerate embeddings and store in ZeroDB in one step. Auto-detects dimension based on model and routes to correct storage. Use when you want to embed text and persist the vectors in a single call. Combines zerodb_generate_embeddings + zerodb_upsert_vector.zerodb_semantic_searchSemantic search using text query (auto-embeds query text). Searches vectors in the same dimension as the model used. Use when searching vectors using a text query (auto-embeds the text). Unlike zerodb_search_vectors which requires a raw vector, this accepts plain text. Unlike zerodb_search_memory which searches agent conversation memory, this searches the general vector store.zerodb_store_memoryStore agent memory in ZeroDB for persistent context. Use when the agent needs to persist conversation turns, decisions, or observations for later recall. Stores with role, session, and agent metadata for filtered retrieval.zerodb_search_memorySearch agent memory using semantic similarity. Use when searching agent conversation memory by natural language. Unlike zerodb_search_vectors which requires a raw vector, and zerodb_semantic_search which searches the general vector store, this searches agent-specific memory entries filtered by session/agent/role.zerodb_get_contextGet agent context window for current session. Use when the agent needs to retrieve its recent conversation context within token limits. Returns the most recent memories for a session, bounded by max_tokens.zerodb_upsert_vectorStore or update a vector embedding with metadata. Supports 384, 768, 1024, or 1536 dimensions. Dimension is auto-detected and validated. Use when you have a pre-computed embedding vector to store or update. For embedding text and storing in one step, use zerodb_embed_and_store instead.zerodb_batch_upsert_vectorsBatch upsert multiple vectors for efficiency. Use when storing many vectors at once to reduce API round-trips. Accepts an array of vector objects and processes them in a single request.zerodb_search_vectorsSearch vectors using semantic similarity. Supports 384, 768, 1024, or 1536 dimension query vectors. Auto-detects dimension. Use when searching raw vector embeddings by similarity with a query vector. Unlike zerodb_semantic_search which accepts text (auto-embeds), this requires a pre-computed vector. Unlike zerodb_search_memory which searches agent memory, this searches the general vector store.zerodb_delete_vectorDelete a specific vector by ID. Use when removing a single vector embedding from the store. WARNING: This operation is irreversible.zerodb_get_vectorRetrieve a specific vector by ID. Use when you need to inspect a particular vector's metadata or embedding values. Optionally includes the full embedding array.zerodb_list_vectorsList vectors in a project/namespace with pagination. Use when the agent needs to browse or enumerate stored vectors, or answer "what vectors exist?". Supports filtering by namespace and metadata.- +73 more on the listing page
Anydb MCP tools 5
db_listList the connection profiles from the anydb config file (~/.anydb/db.json): name, description, driver, which one is the default, and whether it is read-only. Call this first whenever you do not already know a profile name, then pass the name to the other tools as "profile". The result never contains a connection string, a host, a username or a password -- not masked, absent -- because this text goes into your context window and a config file is writable by anyone who can write files. If there is no config file, use "uri" with the other tools instead.db_queryRun one statement against one database (PostgreSQL, MySQL/MariaDB, SQLite, MongoDB or Redis, inferred from the connection). READ-ONLY BY DEFAULT: writes are refused unless "readOnly" is false, and statements that change schema or privileges additionally require "allowDestructive" to be true. Call db_list and db_schema first so table and column names are not guessed, and prefer "params" over inlining values in "query" so the values never appear in the statement text. Put a LIMIT in every query: results are capped anyway, and a cap you did not ask for is how a table gets silently half-read. MongoDB: "collection" is required and "action" picks the operation -- find, count, distinct, aggregate and explain read; insert, update, updateOne, replace, delete and deleteOne write and need "readOnly": false. Prefer the *One actions: one document, not every match. Redis: "query" is a single command such as GET or SCAN.db_schemaDescribe the structure of a database: tables and their columns for SQL, collections with their indexes for MongoDB, keyspace statistics for Redis. Call it before writing a query so names are not guessed -- it is almost always cheaper than a failed query. Runs read-only introspection statements only, never a statement of yours, and "table"/"collection" are bound as parameters wherever the driver allows rather than pasted into SQL. "detail": "full" adds foreign keys, index definitions, primary and unique constraints, row estimates, and inferred field schemas for MongoDB.db_explainReturn the execution plan for a statement WITHOUT running it. Read-only by construction: the statement is planned and not executed, so this is the safe way to catch a sequential scan over a large table and the cheapest way to find a missing index. ANALYZE variants are refused here on purpose, because "EXPLAIN ANALYZE" runs the statement it plans. MongoDB: pass "collection" and a find filter as "query"; a pipeline cannot be explained, use db_query action "aggregate" with a small limit. Redis has no plans, so this tool refuses it.db_healthAsk the database about itself: reachable or not, server version, the role this server authenticated as, whether that role or the server is read-only, object counts, and this server's pool and cache state. Use it instead of guessing at why a connection or a write failed. Note what "readOnly": false does and does not do: it is a request to THIS server, not a security boundary. The boundary is the database role -- a role holding INSERT will succeed whatever these flags say, and a role without them will fail however many are set.
Ready-to-paste client configs
Paste either block (or both) into your client config, e.g. claude_desktop_config.json or ~/.cursor/mcp.json. We only show a config when the install command is confirmed.
ZeroDB MCP Server
{
"mcpServers": {
"ainative-zerodb-mcp-server": {
"command": "npx",
"args": [
"ainative-zerodb-mcp-server"
],
"env": {
"ZERODB_API_URL": "YOUR_ZERODB_API_URL_HERE",
"ZERODB_PROJECT_ID": "YOUR_ZERODB_PROJECT_ID_HERE",
"ZERODB_API_KEY": "YOUR_ZERODB_API_KEY_HERE"
}
}
}
}
Anydb MCP
{
"mcpServers": {
"anydb-mcp": {
"command": "npx",
"args": [
"-y",
"anydb-mcp"
]
}
}
}
Frequently asked questions
ZeroDB MCP Server is categorized under Databases and uses a local stdio subprocess. Anydb MCP belongs to Databases and uses a local stdio subprocess. Pick ZeroDB MCP Server for databases work and Anydb MCP for databases.
Copy the mcpServers block from the config section on this page into your client's config (for example claude_desktop_config.json or ~/.cursor/mcp.json), then fully restart the client.
ZeroDB MCP Server has no declared pricing — check the project's own site. Anydb MCP is listed as free. If a server needs environment variables such as API keys, define them under the env key in your client's MCP config.
Yes. MCP clients support multiple servers: add ainative-zerodb-mcp-server and anydb-mcp as separate keys in the same mcpServers object, and your assistant will call tools from either one.
On AllMCPs, ZeroDB MCP Server has a quality signal of 63/100 (Good) with 1 views, 0 installs and 0 GitHub stars. Anydb MCP has 65/100 (Great) with 5 views, 0 installs and 1 GitHub stars.