Penfield MCP vs SMRITI Memory
A side-by-side look at the Penfield MCP and SMRITI Memory MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.
Verdict: choose Penfield MCP for knowledge & memory work as a local process; choose SMRITI Memory for knowledge & memory as a local process. You can also run both side by side in one mcpServers block.
Which MCP server should you choose?
Choose Penfield MCP when
- You need dedicated capabilities in the Knowledge & Memory domain.
- You prefer a local stdio subprocess transport.
- Its auth model fits you: OAuth 2.0.
Choose SMRITI Memory when
- You need dedicated capabilities in the Knowledge & Memory domain.
- You prefer a local stdio subprocess transport.
- You want tools like
smriti_encode, smriti_recall, smriti_get_context.
Feature & specification comparison
Rows where the two servers differ are marked.
| Spec | ||
|---|---|---|
| Category | Knowledge & Memory | Knowledge & Memory |
| Quality signal | 49/100 · Fair | 53/100 · Good |
| Install command | Confirmed | Confirmed |
| Transport | Local subprocess (stdio) | Local subprocess (stdio) |
| Auth | OAuth 2.0 | Not declared |
| Pricing | Free | Not declared |
| Required env vars | None listed | None listed |
| Verified owner | Community listing | Community listing |
| GitHub stars | 6 | 3 |
| Directory activity | 4 views 0 installs 0 upvotes | 0 views 0 installs 0 upvotes |
| Tools | Not listed | 12 |
| Full listing | View Penfield MCP | View SMRITI Memory |
Tools & capabilities
Penfield MCP tools
No tool names declared yet. Check the project README from the listing page.
SMRITI Memory tools 12
smriti_encodeIngests a new memory. Accept `private=True` to exclude from team syncs.smriti_recallRetrieves memories using semantic and graph-based retrieval.smriti_get_contextHelper to inject the current active working memory slots into the context window.smriti_how_well_do_i_knowPerforms a meta-memory confidence check on a given topic.smriti_knowledge_gapsIdentifies topics the agent has identified it needs more information on.smriti_pinMarks a memory as permanent (protects it from strength decay).smriti_forgetSoft-deletes/archives a memory, leaving a cryptographic tombstone.smriti_consolidateTriggers a background System 2 consolidation run.smriti_statsReturns system-wide statistics (total memories, rooms, private counts).smriti_create_private_roomSpawns a private room. All memories inside this room are visibility-isolated.smriti_open_uiLaunches the interactive visual D3.js memory graph in your default browser.smriti_sync_obsidianExports the Semantic Palace graph structures to markdown files in an Obsidian Vault.
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.
Penfield MCP
{
"mcpServers": {
"penfieldlabs-penfield-mcp": {
"command": "npx",
"args": [
"-y",
"mcp-remote"
]
}
}
}
SMRITI Memory
{
"mcpServers": {
"smriti-memory": {
"command": "uvx",
"args": [
"smriti-memcore"
]
}
}
}
Frequently asked questions
Penfield MCP is categorized under Knowledge & Memory and uses a local stdio subprocess. SMRITI Memory belongs to Knowledge & Memory and uses a local stdio subprocess. Pick Penfield MCP for knowledge & memory work and SMRITI Memory for knowledge & memory.
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.
Penfield MCP is listed as free. Auth: oauth 2.0. SMRITI Memory has no declared pricing — check the project's own site. 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 penfieldlabs-penfield-mcp and smriti-memory as separate keys in the same mcpServers object, and your assistant will call tools from either one.
On AllMCPs, Penfield MCP has a quality signal of 49/100 (Fair) with 4 views, 0 installs and 6 GitHub stars. SMRITI Memory has 53/100 (Good) with 0 views, 0 installs and 3 GitHub stars.