BovedIA — sistema de memoria personal para Claude Code: notas Markdown en tu disco, sincronizadas en la nube
from $15/mo
Nothing to run from here
Memforge is installed from its publisher's own source and answers where it runs, so this marketplace is not in the path of a single call. There is no address here to send one to, and a panel that pretended otherwise would be showing you an answer we made up. Install it and call it from your own client — the Installation tab has the entry for each one.
Open Installation—
p95 latency
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call success
local
runs on your machine
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calls last 7d
What it does
Neuroscience-inspired agent memory — sleep cycles, memory revision, knowledge graph, procedural learning, vector search, and MCP integration
Quickstart
# 1 — run it from where its publisher ships it
npx -y @salishforge/memforge
# 2 — ask your agent something
> Neuroscience-inspired agent memory — sleep cycles, memory revision, knowledge graph, procedural learning, vector search, and MCP integration
Memforge is free: there is no plan to choose, no cap to set and nothing that can bill you.
Publishernot claimed
SAAll 1 server
salishforge1 server
1 category
Collected from a public index. Nobody has claimed this account, so nothing here was written by its author — claim it if it is yours.
Installation
Where are you running it?
Every route below installs the same thing and ends at the same approval screen. This one runs on your machine: your client starts Memforge as a process under your own user, with your files and your network, so the tool surface below is what it can do to your computer rather than to a server somewhere else. It is scanned, signed and pinned to the version you choose — read the surface before you approve it.
Claude Codedeclared by this listing
This is a public server: you run it yourself and this marketplace is not in the path. Claude Code registers it in one command.
claude mcp add memforge-mcp -- npx -y @salishforge/memforgeReconnect, or start a new session, and the tools appear in the model’s tool list.
Free to install, and it runs from its publisher’s own package: no account, no key, no card.
What it asks of you
It reaches a system of yours, so it needs your own credential rather than the publisher’s: MEMFORGE_URL, MEMFORGE_TOKEN. You set them after installing; the value is sealed here and sent to the server on each call.
What it writes
One config entry your client uses to start the process locally. A local server runs with your file system and your network, which is why it is priced without metering.
What you approve
45 tools, with what each one reads, writes and reaches shown before you agree — the same list on every route above. Read the tool surface.
Tool surface
What the model actually sees. Descriptions are diffed on every release — see version history.
Store a memory event for an agent. Returns the created memory ID.
Takes no parameters.
Example callreturns →
Search an agent
Takes no parameters.
Example callreturns →
Consolidate hot-tier events into searchable warm-tier memories.
Takes no parameters.
Example callreturns →
Proactively surface relevant memories and procedures for a given context.
Takes no parameters.
Example callreturns →
Get session resumption context: recent memories, procedures, contradictions.
Takes no parameters.
Example callreturns →
Record whether retrieved memories were helpful (positive/negative/neutral).
Takes no parameters.
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Run a sleep cycle: score, triage, revise, maintain graph, reflect.
Takes no parameters.
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Get memory health metrics: importance, confidence, revision velocity.
Takes no parameters.
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Get memory tier statistics: hot, warm, cold counts.
Takes no parameters.
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Retrieve memories in chronological order within an optional time range.
Takes no parameters.
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Search knowledge graph entities (people, systems, organizations, concepts).
Takes no parameters.
Example callreturns →
Traverse the knowledge graph from a specific entity. Returns connected nodes and edges.
Takes no parameters.
Example callreturns →
Trigger a reflection — synthesizes insights and contradictions from recent memories.
Takes no parameters.
Example callreturns →
Retrieve stored reflections (synthesized insights from past reviews).
Takes no parameters.
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Retrieve learned procedures — condition→action rules extracted from reflections.
Takes no parameters.
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Trigger meta-reflection — synthesizes higher-order principles from accumulated first-order reflections.
Takes no parameters.
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Detect and merge duplicate entities in the knowledge graph using trigram similarity.
Takes no parameters.
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Search archived (cold tier) memories. Use for audit, recovery, and compliance. Returns rows still within retention window.
Takes no parameters.
Example callreturns →
Restore a cold tier row to warm tier for reactivation. Non-destructive — the cold row is preserved for audit.
Takes no parameters.
Example callreturns →
Get an adaptive sleep-cycle recommendation. Advisory only — MemForge has no built-in scheduler. Callers (cron jobs, control planes) read the urgency and reason and decide whether to call memforge_sleep.
Takes no parameters.
Example callreturns →
Publish an agent\
Takes no parameters.
Example callreturns →
List active procedures shared in a pool, ranked by confidence and corroboration. Use to discover what condition→action rules other agents have learned.
Takes no parameters.
Example callreturns →
Discover which pool members know the most about a topic. Returns agents ranked by relevance score with sample matching memories. Use to route questions to the right agent.
Takes no parameters.
Example callreturns →
Declare an expertise domain for an agent. Roles are used by expertise discovery and for routing queries in multi-agent systems. Upserts on (agent_id, domain).
Takes no parameters.
Example callreturns →
Get all declared expertise roles for an agent, ordered by confidence. Includes both manually declared and auto-detected roles.
Takes no parameters.
Example callreturns →
Auto-detect expertise roles from an agent\
Takes no parameters.
Example callreturns →
Set or clear the validity window on a warm-tier memory. Memories past valid_until are penalized during sleep cycles.
Takes no parameters.
Example callreturns →
Record the outcome of executing a procedure. Success/failure counts drive confidence evolution during sleep cycles.
Takes no parameters.
Example callreturns →
Fetch drift-detection report based on recent drift_signals snapshots. Trend classification: stable | degrading | recovering | insufficient_data.
Takes no parameters.
Example callreturns →
Mark a namespace as deprecated. Sleep cycles will actively decay importance and confidence of memories in this namespace each cycle, eventually evicting them. Reversible.
Takes no parameters.
Example callreturns →
Reverse a namespace deprecation. Future sleep cycles stop decaying its rows.
Takes no parameters.
Example callreturns →
List the agent
Takes no parameters.
Example callreturns →
Enqueue a dream run — async sleep-cycle job mirroring Anthropic Claude Dreaming. Returns a run id (status=
Takes no parameters.
Example callreturns →
Fetch a dream run by id. Useful for polling pending or running cycles.
Takes no parameters.
Example callreturns →
List dream runs for an agent. Filter by status or source.
Takes no parameters.
Example callreturns →
Request cancellation of a dream run. Pending runs go straight to
Takes no parameters.
Example callreturns →
Bridge: export warm-tier rows for an agent/namespace to an Anthropic Memory Store. Requires DREAMS_PROVIDER=anthropic + ANTHROPIC_API_KEY on the server.
Takes no parameters.
Example callreturns →
Bridge: import records from an Anthropic Memory Store into warm_tier. Strategies: anthropic-wins (default — overwrite), memforge-wins (insert net-new only), merge (overwrite content, preserve local metadata).
Takes no parameters.
Example callreturns →
Bridge: report current sync state for an agent/namespace — known store links, last push/pull timestamps, and a drift indicator (warm rows newer than the most recent push).
Takes no parameters.
Example callreturns →
Return the count of warm-tier memories per epistemic_status for an agent. Useful for gauging how much of the knowledge base is well-corroborated (established) vs. newly accepted (provisional) vs. uncertain (contested/inferred/deprecated).
Takes no parameters.
Example callreturns →
Explain a warm-tier memory
Takes no parameters.
Example callreturns →
Traverse causal relationships from a warm-tier memory. Returns a chain of cause/effect memories with edge strength and confidence.
Takes no parameters.
Example callreturns →
Predict probable next events for a context, based on causal edges mined from memory sequences. Probability is a relative ranking signal (confidence-scaled, monotonic in edge strength), not a calibrated probability.
Takes no parameters.
Example callreturns →
Retrieve an agent
Takes no parameters.
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Return an agent
Takes no parameters.
Example callreturns →
Freeyour plan
$0 forever
- Every tool, no call limit
- No card, no account needed
- Source published under a licence you can read
- Runs on your machine — nothing of it reaches our gateway
- Nothing to cap, because nothing bills
What counts against your monthly calls
| Tool | Unit | Calls used | Out of the allowance |
|---|
Nothing here is billable. Memforge costs nothing to install and nothing to call, at any volume.
Call allowance · this installenforced at the gateway
Monthly allowance, in calls
—
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Alert at 80% · then the tool returns a normal MCP error
Used this month: $8.42
$16.58 left
ATrust score 97 / 100
Release 3.0.0-beta.4 · scanned 26 Aug 2026
Two independent axes, because powerful and malicious are different questions. The grade is threat only. The capability level is blast radius, and it is never a penalty on the grade — it is priced as one subtract-only term in the score, where you can see it.
Threat score100
Client score97
Findings1 threat · 0 capability
Capabilitymoderate
Coveragesource
Verificationsource
Surface digestf97e43d52fff5487b6745da8c71babc76110c19c50df14cc3d524ff85a434131
Score vectorthreat 100 → client 97
| Term | Level | What it prices | Points |
|---|---|---|---|
| capability-exposure | moderate | capability blast radius (moderate) — client exposure if the model is manipulated | −3 |
| verification-discount | source | publisher verification (provenance) — cryptographic build provenance ties the artifact to its source | −0 |
| coverage-honesty | source | inspection depth (source) — how much of the target the scan could see | −0 |
score = clamp(round(threatScore − E_cap − E_ver − E_cov), 0, 100). No model, no opinion, no network call at scoring time: the same methodology version against the same bytes always produces this number, and every line above is a field of the report rather than a summary of it.
What the scan could actually read
A grade is only as meaningful as its coverage, so the scanner publishes its own depth before it publishes its result.
Tool surfacenot available
Implementation sourceread
Package metadataread
Live transportnot available
No tools were enumerated, so prompt-injection, capability and toxic-flow analysis had no tool surface to inspect. To grade a package’s real runtime tools, scan the running server: --command "npx -y <package>".
Capability — what it could do if the model were manipulated
Tags derived from each tool’s schema and the implementation, not from what the tool calls itself. moderate is the level these add up to.
| Tool | Capability tags | Why the tag was assigned |
|---|---|---|
| No per-tool rows for this release — see the note below. | ||
can send data / act on an external service
Toxic-flow graph
The lethal trifecta, checked as a graph rather than as a checklist: untrusted input, a sensitive source and an external sink have to meet before there is a path worth worrying about.
The public result for this release does not print the flow graph, so there is nothing to show here. That is not the same as "no paths were found": what the scan did read is above, under coverage.
Supply chain and provenance
Integrityfirst-seen
Surface digestf97e43d52fff5487
Scanned2026-08-26
This is the first scan of this surface here, so there is nothing yet to compare it against.
Every result on this tab comes from one deterministic pass over the published package — offline, rule by rule, and auditable line by line above. Same methodology version, same bytes, same score.
Release history
Pinned to 3.0.0-beta.4 — the install command below asks for that release. A pin is part of an install, so it is kept for this visit and written down when you install.
3.0.0-beta.4
undated
installedNo release note was published with this version.
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no reviews yet
Reviews are earned
Only accounts with at least 50 real tool calls against this server in the last 90 days can post. Ratings are weighted by how much the reviewer actually uses it, and publishers can reply once per review.
Reviews are earned
Writing one takes an account with at least 50 real tool calls against Memforge in the last 90 days. That is the whole gate — there is no other way to post, which is why the counts beside each review are worth reading.
No reviews yet
Nobody has reviewed this listing. The rating on the card is the mean of the reviews written here and nothing else, so there is no rating until somebody writes the first — which takes an account with 50 real tool calls against it.