Code Index vs FactMem — MCP Server Comparison | AllMCPs
Side-by-Side Model Context Protocol Comparison
Code Index vs FactMem
In-depth architectural comparison of the Code Index and FactMem MCP servers. Compare execution transports, security boundaries, tool capabilities, quality scores, and ready-to-paste client installation snippets for Claude, Cursor, Windsurf, and VS Code.
At a Glance & Executive Verdict
Code Index
Databases · Local stdio
Quality: 63/100 (Good) | Auth: No auth required
FactMem
Databases · Local stdio
Quality: 53/100 (Good) | Auth: No auth required
Verdict Summary: Choose Code Index if you need specialized Databases tools running via a local process. Choose FactMem if your workspace requires Databases integration with local subprocess execution. Both servers can be configured concurrently in your client's mcpServers manifest.
Which MCP Server Should You Choose?
Choose Code Index when:
You need dedicated capabilities in the Databases domain.
You prefer local stdio subprocess transport architecture.
Your security boundary fits: No auth required (Free / Open Source).
Full-text search across functions (name, docstring, body)
search_class
Full-text search across classes
get_function
Get function by exact name (case-insensitive fallback; **(v0.44.0)** on 0 matches returns `did_you_mean` with similar names)
get_class
Get class by exact name (case-insensitive fallback; **(v0.44.0)** on 0 matches returns `did_you_mean` with similar names)
get_object_structure
Structure of a 1C object. **v0.63.0:** object templates are now in the registry — a row `Catalog.X.Template.Y` with the owner, the template kind and a `content_indexed` flag (large templates stay out of the index, yet the template itself is visible and findable by name)
Ready-to-Paste Client Configurations
Paste either (or both) of these JSON server blocks into your client config file (e.g. claude_desktop_config.json or ~/.cursor/mcp.json).
Code Index is categorized under Databases and uses a local stdio subprocess. In contrast, FactMem belongs to Databases using local stdio subprocess. Select Code Index when you need capabilities focused on databases and FactMem when you require tools for databases.
Who calls this function? **(v0.35.0)** each row carries the caller's source `path` (distinguishes same-named callers from different files). **v0.62.0:** for 1C configurations, form event handler bindings (`kind: form_binding`) are added to the code callers — such a procedure is run by the platform…
get_callees
What does this function call? **(v0.35.0)** each row carries the source `path
find_path
(v0.23.0)** Shortest path in the call graph between two functions `from`→`to` (iterative cycle-safe BFS over unique `calls` nodes, `max_depth=5`, any language). Returns path edges `[{caller, callee, line}]`. **v0.57.0:** an empty answer carries walk cut-off flags `walk_depth_exhausted` / `walk_node…
get_call_tree
(v0.23.0)** Call tree from a `root` function up to `max_depth` (default 3). `direction`: `callees`/`down` (downstream) or `callers`/`up`. Flat edge list `[{caller, callee, line, depth, path}]` (**(v0.35.0)** `path` = source file of each edge) + nested `{name, children}` tree; `max_nodes` cap
Working briefing (the same markdown as `memory://briefing`) plus facts captured in this session. Call at the start of every conversation if the client does not load resources.
get_entity
Everything known about any named subject — person, organisation, project, place, product — and how it connects. When several rows share the name under different types, facts from all of them come back. Hyphens, underscores, and stray punctuation count as the same letters only when that does not joi…
get_context
Everything relevant to a topic (search + entity traversal)
search_knowledge
Hybrid search across integrated knowledge
capture_fact
Store a fact. On a copy store this is a correction for something extraction missed; on a store with empty `sources` it is how facts get in. The description the assistant sees is generated from that same rule.
consolidate
Integrate pending facts into long-term knowledge. Extracts entities, resolves duplicates, detects contradictions, builds the knowledge graph.